A method, an apparatus, a device, and a medium for managing code data are provided. In the method, an application programming interface associated with a merge request is determined in response to receiving the merge request for merging first code data into second code data. An interface definition of the application programming interface is obtained, and the interface definition describes at least one data item specified in the application programming interface. Annotation data associated with the at least one data item is added to the interface definition, and the annotation data describes the at least one data item in accordance with a code specification of a code management platform. The second code data is committed to the code management platform based on the interface definition.
Embodiments in the disclosure provides a method, apparatus, device and storage medium for application processing. A method includes: receiving a first chat message from a user in a chat window of the user and a digital assistant, the first chat message indicating a user requirement for creating or adjusting a target application; determining, based on capability information related to an application processing capability of an application creation platform and interaction information in the chat window, a plurality of sub-requirements comprised in the user requirement; and performing the application processing operation associated with the plurality of sub-requirements in response to receiving a confirmation of the plurality of sub-requirements from the user.
Provided are a method and apparatus for managing code data, a device, and a medium. The method comprises: in response to receiving a merge request for merging first code data to second code data, determining an application programming interface associated with the merge request; acquiring an interface definition of the application programming interface, the interface definition describing at least one data item specified in the application programming interface; adding annotation data associated with the at least one data item to the interface definition, the annotation data describing the at least one data item in accordance with code specifications of a code management platform; and submitting the second code data to the code management platform on the basis of the interface definition. By means of the implementation of the present disclosure, in a code management platform, at least one data item can be automatically described in accordance with a code specification on the basis of annotation data. In this way, the workload of manual annotation can be reduced, and the potential risk of code data being unavailable due to manual errors can be avoided.
According to embodiments of the present disclosure, a method, an apparatus, a device, and a storage medium for task execution are provided. In the method for task execution, a task to be executed is determined based on a user intent identified from a user input. A set of functional blocks is determined based on a plurality of functional blocks and a data flow associated with the task. The task is executed using the combined set of functional blocks. In this way, the user needs may be understood, and the indicated task may be conveniently and flexibly completed by combining the set of functional blocks.
A method, an apparatus, a device and a storage medium for test case generation are provided. The method includes: receiving a test case generation request for at least one functional block in an application; obtaining a data structure declaration related to a test case of the at least one functional block in response to the test case generation request; and generating, using a model, a plurality of test cases for the at least one functional block at least based on the data structure declaration and logical architecture information of the at least one functional block.
The present disclosure relates to an image segmentation method and apparatus, a medium, and an electronic device, belonging to the field of computer technologies, which can effectively alleviate the dependence of a segmentation task on manual pixel-level fine annotation, ensure accurate image semantic segmentation, and solve the problems of excessive noise in a segmented image and inaccurate boundaries. The image segmentation method includes: receiving an image to be segmented input by a user and a text description for the image to be segmented; clustering, by using a clustering module in an image semantic segmentation model, regions having a spatial similarity relationship in the image to be segmented to obtain clustering regions; and obtaining a segmentation result by using a segmentation module in the image semantic segmentation model based on the text description, the image to be segmented, and the clustering regions.
G06V 10/26 - Segmentation de formes dans le champ d’imageDécoupage ou fusion d’éléments d’image visant à établir la région de motif, p. ex. techniques de regroupementDétection d’occlusion
G06V 10/762 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant le regroupement, p. ex. de visages similaires sur les réseaux sociaux
G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p. ex. des objets vidéo
G06V 10/77 - Traitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source
G06V 10/776 - ValidationÉvaluation des performances
The present disclosure involves methods, apparatus, and systems for automated failure analysis of software in an isolated environment. This can include identifying, from an error log, a set of errors generated during code execution in an isolated computing environment; parsing the set of errors to categorize each particular error into a first category of errors or a second category of errors; and for each error in the second category of errors: generating a summary of the error; identifying a portion of code causing the error; removing sensitive information from the portion of code to create masked portion of error code; and sending a message to an external system outside the isolated computing environment, the message comprising the summary and the masked portion of error code.
Provided in the embodiments of the present disclosure are a content generation method and apparatus. The method comprises: acquiring style information associated with a card component to be generated; providing the style information to a first model, so as to generate code content corresponding to said card component; providing service specification information associated with said card component to a second model, so as to adjust the code content; and providing access information corresponding to the adjusted code content. In this way, the embodiments of the present disclosure can perform multi-round communication with the first model and the second model (equivalent to providing various information) to generate card components, thereby effectively improving the generation efficiency and generation quality of card components.
Provided are a speech processing method and apparatus, and an electronic device. The method includes: displaying an accent conversion page, where the accent conversion page includes an accent control associated with a target accent, and a speech obtaining control; determining an identifier of the target accent in response to a touch operation on the accent control; obtaining first speech in response to a touch operation on the speech obtaining control, where the target accent is different from an accent of the first speech; performing accent conversion on the first speech based on the first speech and the identifier of the target accent, to obtain second speech, where an accent of the second speech is the target accent, the accent conversion is implemented based on a speech processing model, and the speech processing model is obtained through training based on sample speech of non-parallel data; and playing the second speech.
G10L 21/007 - Changement de la qualité de la voix, p. ex. de la hauteur tonale ou des formants caractérisé par le procédé utilisé
G06F 3/0484 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs
G06F 3/0488 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] utilisant des caractéristiques spécifiques fournies par le périphérique d’entrée, p. ex. des fonctions commandées par la rotation d’une souris à deux capteurs, ou par la nature du périphérique d’entrée, p. ex. des gestes en fonction de la pression exercée enregistrée par une tablette numérique utilisant un écran tactile ou une tablette numérique, p. ex. entrée de commandes par des tracés gestuels
G10L 15/02 - Extraction de caractéristiques pour la reconnaissance de la paroleSélection d'unités de reconnaissance
G10L 15/06 - Création de gabarits de référenceEntraînement des systèmes de reconnaissance de la parole, p. ex. adaptation aux caractéristiques de la voix du locuteur
The present disclosure involves methods, apparatus, and systems for sending, from a developer portal system and to an issue repository, a request for an issue stack, wherein the issue stack is a report generated in response to a user experiencing a software issue; receiving the issue stack; sending the issue stack and an issue ID to an analysis engine to be analyzed; identifying a bot to analyze the issue stack, wherein the selected bot comprises a first machine learning algorithm; generating a prompt for a generative AI model, the prompt comprising the issue stack; sending the prompt to a generative AI model; receiving a response from the generative AI model; generating an analysis result based on the response from the generative AI model; and sending the analysis result to the developer portal system for presentation at a user interface associated with the developer portal system.
G06F 11/07 - Réaction à l'apparition d'un défaut, p. ex. tolérance de certains défauts
G06F 11/22 - Détection ou localisation du matériel d'ordinateur défectueux en effectuant des tests pendant les opérations d'attente ou pendant les temps morts, p. ex. essais de mise en route
Embodiments of the present disclosure provide a method, apparatus, device and storage medium for question answering. The method for question answering comprises: in response to detecting a question answering initiation, capturing image data and speech data using a device of a user, the speech data indicating an intent related to a question; determining an answer corresponding to the question from the image data according to the intent; and outputting the answer at least in form of speech.
G06V 10/40 - Extraction de caractéristiques d’images ou de vidéos
G06V 10/70 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique
G06V 10/98 - Détection ou correction d’erreurs, p. ex. en effectuant une deuxième exploration du motif ou par intervention humaineÉvaluation de la qualité des motifs acquis
G10L 15/18 - Classement ou recherche de la parole utilisant une modélisation du langage naturel
39 - Services de transport, emballage et entreposage; organisation de voyages
Produits et services
(1) Delivery of goods by courier; information and advisory services in the field of the delivery of goods by courier; locating and tracking of cargo for transportation purposes; tracking and tracing of packages in transit; loading and unloading of cargo; providing information in the field of cargo unloading services; courier services; packing, crating and warehousing services; providing information about warehouse storage services; rental of warehouses; storage of goods for others; warehouse storage services; rental and leasing of storage containers; rental of pallets; transportation logistics services, namely, arranging the transportation of goods for others; packaging of goods; expedited shipping and logistics services, namely, expedited parcel shipping services for ground, air and cross-border shipments; transportation logistics services, namely, planning and scheduling shipments for users of transportation services; supply chain logistics and reverse logistics services, namely, storage, transportation and delivery of goods for others by air, rail, ship or truck; parcel collection services; packaging of articles and goods to the order and specification of others.
13.
GRAPH NEURAL NETWORK-BASED MODEL TRAINING METHOD AND APPARATUS
The present disclosure provides a model training method based on a graph neural network, and the method includes: acquiring a first training graph and a label corresponding to the first training graph, wherein the first training graph is a relationship graph corresponding to training multimedia content, or the first training graph is a relationship graph corresponding to a training item; obtaining a position feature, a structure feature, and a node feature of the first training graph based on the first training graph; fusing the position feature, the structure feature, and the node feature, to obtain a fused feature; and training a target model based on the GNN according to the fused feature and the label.
The disclosure provides a folded optical path lens, an optical imaging system, and a head-mounted display device. The folded optical path lens includes: a first lens, which has a first surface and a second surface arranged opposite each other, with the first surface being a convex surface; a beam splitter film, which is disposed on the first surface. The difference between the reflectance and transmittance of the beam splitter film is less than or equal to 20%. The beam-splitting film comprises a plurality of optical coating layers stacked together, wherein the plurality of optical coating layers comprise at least one non-metallic transparent coating and at least one metallic layer.
Embodiments of the present disclosure relate to an interface interaction method and apparatus, a device, and a storage medium. The method comprises: presenting an interactive interface, the interactive interface comprising an input control for inputting a prompt (410); detecting whether information inputted in the input control comprises a target field of a preset type (420); in response to the inputted information comprising the target field of the preset type, adjusting a display style of the target field in the input control (430); and in response to receiving a preset operation for the target field, providing auxiliary information associated with the target field (440). The embodiments of the present disclosure can improve the quality of an inputted prompt.
A display module and a near-eye display device. The display module comprises: a display assembly (21); a lens (22) located on a display side of the display assembly (21) and used for imaging a display image of the display assembly (21); and a light source assembly (23) located in an edge region of the lens (22) and used for emitting infrared light, the infrared light being used for eye tracking imaging.
Described herein are techniques for creating graphs. A type of connection node applicable to the graphs is created in response to receiving user input. The type of connection node is configured to transmit data and not to process data. The type of connection node is configured to switch positions of input and output ports of the connection node. A graph comprises a plurality of data nodes configured to process data. The graph comprises a plurality of edges connecting the plurality of data nodes. At least one connection node is added into an edge of the graph to adjust the edge's position. Adjustments to the graph are implemented by utilizing the at least one connection node..
G06F 3/04845 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs pour la transformation d’images, p. ex. glissement, rotation, agrandissement ou changement de couleur
18.
ADVERSARIAL TRAINING OF A MODEL FOR QUESTION ANSWERING
Embodiments of the present disclosure provide a solution for adversarial model training. A method includes: generating a prompt input using an adversarial machine learning model; providing the prompt input to a target machine learning model, to generate a response to the prompt input; determining a first reward score for the response with respect to the prompt input; and fine-tuning the target machine learning model according to a first optimization objective, the first optimization objective being configured to increase or maximize the first reward score for the target machine learning model.
According to embodiments of the disclosure, a method, apparatus, device and storage medium for signal processing are provided. The method includes capturing, using a camera, a first image for a first portion of a user, the first image having a first precision; performing biometric-based identity verification on the user using information of the first portion comprised in the first image; and in response to the identity verification being passed, obtaining at least one second image for a second portion of the user, the at least one second image having a second precision different from the first precision.
Embodiments of the present disclosure disclose a model quantization method and apparatus, an electronic device, and a storage medium. The method includes: determining a capability metric of a respective module in a model to be quantized, wherein the capability metric of the respective module indicates capability of the respective module in data processing; determining a difference value in capability metrics between adjacent modules in modules and determining an adjacent module pair to be joined according to the difference value; and performing joint quantization on the determined adjacent module pair to be joined in the model to be quantized.
According to embodiments of the present disclosure, provided are a material generating method and apparatus. The method comprises: in response to a preset operation received in a media editing interface, presenting a material generating interface, wherein the material generating interface comprises a canvas component; in response to a first interaction operation received via the canvas component, presenting, in the canvas component, graphical content corresponding to the first interaction operation; presenting, in a preview component of the media editing interface, a first material generated on the basis of the graphical content; and in response to a second interaction operation received via the material generating interface, adding a target material determined on the basis of the first material to the media editing interface. In this way, the embodiments of the present disclosure can effectively improve material generating efficiency.
G06F 3/0481 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p. ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comportement ou d’aspect
22.
METHOD AND APPARATUS FOR GENERATING SPECIAL EFFECTS, AND DEVICE AND STORAGE MEDIUM
According to the embodiments of the present disclosure, provided are a method and apparatus for generating special effects. The method comprises: on the basis of received asset description text, generating a set of interactive assets for placement in a virtual scene; generating code content associated with at least one interactive asset in the set of interactive assets, wherein the code content describes interaction logic associated with the at least one interactive asset; and on the basis of at least the code content, creating a special effects file, wherein the special effects file is configured to provide special effects associated with an augmented reality scene, and the augmented reality scene is created on the basis of acquired image data. In this way, the embodiments of the present disclosure can effectively improve the efficiency of generating special effects.
An optical system and a display device. The optical system comprises a prism assembly, wherein the prism assembly comprises a plurality of light incident surfaces and one light exit surface, each light incident surface being configured to allow incidence of image light of one color, different light incident surfaces being configured to allow incidence of image light of different colors, and the image light of different colors being converged in the prism assembly and then exiting from the light exit surface. The number of prisms comprised in the prism assembly is less than four, and the prism assembly comprises at least a first prism and a second prism. A first surface of the first prism is disposed opposite a second surface of the second prism. A microstructure array is provided between the first surface and the second surface, and the microstructure array is configured to change the propagation direction of image light of at least one color and transmit image light of at least another color.
09 - Appareils et instruments scientifiques et électriques
35 - Publicité; Affaires commerciales
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable computer search engine software; Downloadable intelligent personal assistant software for information search, information recommendation and question answering; Downloadable intelligent personal assistant software for generating report, conducting research, question answering based on uploaded documents, images, audio, video, text; Downloadable enterprise software in the nature of a database for non-transactional data and a search engine for database content; Downloadable computer software for integrating and processing proprietary content and product data to deliver intent-based results; Downloadable electronic databases in the field of artificial intelligence, deep learning, virtualization and machine learning; Downloadable computer software for memorizing, querying, analyzing, processing the uploaded documents, audio, video, text and images in order to conduct training for the artificial intelligence agent; Downloadable computer software for use in vector database management; Downloadable computer software for collecting, analyzing, organizing, extracting and transforming data for use with vector databases and large language model frameworks; Downloadable computer software for artificial intelligence and machine learning, voice recognition, image recognition and processing, graphics recognition and processing, text recognition and processing, speech analytics, generating images and videos from text, speech to text conversion, text to speech conversion, searching, licensing, purchasing and downloading digital content, accessing, browsing and searching online databases, the integration of artificial intelligence and machine learning in the field of Big Data; Downloadable interactive software for use in vector database management; Downloadable computer software for providing a unified platform for multimodal search, personalised recommendations, and conversational content discovery Collection and compilation of information into computer databases in the field of artificial intelligence, deep learning, virtualization and machine learning; Providing business information, namely, commercial corporate and statistical information provided on-line from a computer database or the Internet; Collection and systematisation of information into computer databases; Updating and maintenance of data in computer databases; Virtual executive assistant services for others; Database management services; Business advisory services in the field of artificial intelligence, deep learning, virtualization and machine learning Cloud storage services for electronic data; Database development services; Providing online non-downloadable virtual assistant software using artificial intelligence (AI) for information search, information recommendation and question answering; Providing online non-downloadable virtual assistant software using artificial intelligence (AI) for generating report, conducting research, question answering based on uploaded documents, images, audio, video, text; Providing temporary use of on-line non-downloadable software for memorizing, querying, analyzing, processing the uploaded documents, audio, video, text and images in order to conduct training for the artificial intelligence agent; Cloud computing featuring software for use in memorizing, querying, analyzing, processing the uploaded documents, audio, video, text and images in order to conduct training for the artificial intelligence agent; Providing online non-downloadable computer software platforms for collecting, analyzing, organizing, extracting and transforming data for use with vector databases and large language model frameworks; Providing temporary use of on-line non-downloadable open-source software for producing, storing, arranging, classifying, organizing, searching, identifying, collecting, filtering, processing, visualizing, reporting, managing and analyzing data; Platform as a service (PAAS) featuring computer software platforms for collecting, analyzing, organizing, extracting and transforming data for use with vector databases and large language model frameworks; Providing temporary use of on-line non-downloadable software for artificial intelligence and using artificial intelligence for machine learning, voice recognition, image recognition and processing, graphics recognition and processing, text recognition and processing, speech analytics, generating images and videos from text, speech to text conversion, text to speech conversion, searching, licensing, purchasing and downloading digital content, accessing, browsing and searching online databases; Providing temporary use of on-line non-downloadable software for the integration of artificial intelligence and machine learning in the field of Big Data
05 - Produits pharmaceutiques, vétérinaires et hygièniques
09 - Appareils et instruments scientifiques et électriques
38 - Services de télécommunications
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
(1) Operating system program for AI and machine learning, voice recognition, image recognition and processing, graphics recognition and processing, text recognition and processing, speech analytics, generating images from text, speech to text conversion, text to speech conversion, searching, licensing, purchasing and downloading digital content, accessing, browsing and searching online databases, the integration of artificial intelligence and machine learning in the field of Big Data; downloadable computer software used in the field of deep learning for data collection, analysis, and collation for AI and machine learning, voice recognition, image recognition and processing, graphics recognition and processing, text recognition and processing, speech analytics, generating images from text, speech to text conversion, text to speech conversion, searching, licensing, purchasing and downloading digital content, accessing, browsing and searching online databases, the integration of artificial intelligence and machine learning in the field of Big Data; downloadable chat robot software used for simulation dialogue for AI and machine learning, voice recognition, image recognition and processing, graphics recognition and processing, text recognition and processing, speech analytics, generating images from text, speech to text conversion, text to speech conversion, searching, licensing, purchasing and downloading digital content, accessing, browsing and searching online databases, the integration of artificial intelligence and machine learning in the field of Big Data; computer operating software for AI and machine learning, voice recognition, image recognition and processing, graphics recognition and processing, text recognition and processing, speech analytics, generating images from text, speech to text conversion, text to speech conversion, searching, licensing, purchasing and downloading digital content, accessing, browsing and searching online databases, the integration of artificial intelligence and machine learning in the field of Big Data; computer program (downloadable software) for AI and machine learning, voice recognition, image recognition and processing, graphics recognition and processing, text recognition and processing, speech analytics, generating images from text, speech to text conversion, text to speech conversion, searching, licensing, purchasing and downloading digital content, accessing, browsing and searching online databases, the integration of artificial intelligence and machine learning in the field of Big Data; downloadable mobile applications for AI and machine learning, voice recognition, image recognition and processing, graphics recognition and processing, text recognition and processing, speech analytics, generating images from text, speech to text conversion, text to speech conversion, searching, licensing, purchasing and downloading digital content, accessing, browsing and searching online databases, the integration of artificial intelligence and machine learning in the field of Big Data; computer software applications, downloadable for AI and machine learning, voice recognition, image recognition and processing, graphics recognition and processing, text recognition and processing, speech analytics, generating images from text, speech to text conversion, text to speech conversion, searching, licensing, purchasing and downloading digital content, accessing, browsing and searching online databases, the integration of artificial intelligence and machine learning in the field of Big Data; computer software, recorded for AI and machine learning, voice recognition, image recognition and processing, graphics recognition and processing, text recognition and processing, speech analytics, generating images from text, speech to text conversion, text to speech conversion, searching, licensing, purchasing and downloading digital content, accessing, browsing and searching online databases, the integration of artificial intelligence and machine learning in the field of Big Data; Speakers; headphones; smart glasses; smart watches; smart wristbands; smartphone; tablet; Software; computer software; downloadable communication software for instant messaging and for the electronic transmission of text, voice, images and video among users; interactive software; downloadable telecommunications software for the transmission of data, voice, images and video over communication networks; artificial intelligence software; downloadable computer software applications for use with artificial intelligence for natural language processing, generating text and generating images from text; downloadable computer chatbot programs and software for simulating conversations with artificial intelligence; downloadable computer programs and software using artificial intelligence for data analysis; downloadable chatbot computer programs and software for simulating conversations with users using artificial intelligence; downloadable computer programs and downloadable computer software for the artificial production of human speech and text; downloadable computer programs and downloadable computer software for natural language processing, generation, understanding and analysis; downloadable computer programs and downloadable computer software for machine-learning based language and speech processing software; downloadable computer programs and downloadable computer software for creating and generating text; downloadable computer programs and downloadable computer software for creating and generating images from text; downloadable software in the nature of a mobile application for creating and editing photographs and for recording and editing videos using AI; downloadable computer software in the nature of an artificial intelligence model for performing generative text AI tasks and natural language processing AI tasks and for writing content based on a theme, summarizing text, document question-answering and simulating natural conversation; downloadable software in the nature of a downloadable mobile application featuring an artificial intelligence model for performing generative text AI tasks and natural language processing AI tasks and for writing content based on a theme, summarizing text, document question-answering and simulating natural conversation; downloadable electronic publications in the nature of articles, research papers, reports, and newsletters in the fields of artificial intelligence, computer science, and computer software design and development. (1) Electronic message sending; transmission of sound, video and information; transmission of digital files; computer-aided transmission of data, information, messages, and images; network transmission of sounds, images, signals and data; streaming of data; providing online forums; communications by computer terminals; communication of information by computer; communication services, namely, electronic transmission of data among users of computers; providing multiple-user access to a global computer information network; providing access to databases; providing Internet access; computer aided transmission of messages and images; communications by computer; transmission of computer data; computer aided transmission of data; computer aided transmission of images; computer-aided transmission of information; computer aided transmission of messages; providing user access to a global computer network; provision of access to computer databases; provision of telecommunication access to computer databases; transfer of information via computer networks; providing access via data networks to software for Internet access.
(2) Providing on-line non-downloadable software for AI and machine learning, voice recognition, image recognition and processing, graphics recognition and processing, text recognition and processing, speech analytics, generating images from text, speech to text conversion, text to speech conversion, searching, licensing, purchasing and downloading digital content, accessing, browsing and searching online databases, the integration of artificial intelligence and machine learning in the field of Big Data; Application service provider (ASP) services featuring computer software for AI and machine learning, voice recognition, image recognition and processing, graphics recognition and processing, text recognition and processing, speech analytics, generating images from text, speech to text conversion, text to speech conversion, searching, licensing, purchasing and downloading digital content, accessing, browsing and searching online databases, the integration of artificial intelligence and machine learning in the field of Big Data; providing online non-downloadable chatbot software for AI and machine learning, voice recognition, image recognition and processing, graphics recognition and processing, text recognition and processing, speech analytics, generating images from text, speech to text conversion, text to speech conversion, searching, licensing, purchasing and downloading digital content, accessing, browsing and searching online databases, the integration of artificial intelligence and machine learning in the field of Big Data; Software as a service (SaaS) services featuring software for AI and machine learning, voice recognition, image recognition and processing, graphics recognition and processing, text recognition and processing, speech analytics, generating images from text, speech to text conversion, text to speech conversion, searching, licensing, purchasing and downloading digital content, accessing, browsing and searching online databases, the integration of artificial intelligence and machine learning in the field of Big Data; providing search engines for the internet; research and development services in the field of artificial intelligence; Software as a service (SaaS) services featuring software for generating images from text; software as a service (SaaS) services featuring software providing for searching, licensing, purchasing and downloading digital content; providing a website featuring non-downloadable software using artificial intelligence for generating images from text; software as a service (SAAS) services featuring software using artificial intelligence and a hybrid computer learning system for subjective statistical analysis and subjective predictive analysis; providing online non-downloadable software for the artificial production of human speech and text; providing online non-downloadable software for natural language processing, generation, understanding and analysis; providing online non-downloadable software for machine-learning based language and speech processing software; providing online non-downloadable chatbot software for simulating conversations; providing online non-downloadable software for creating and generating text; providing online non-downloadable software for creating and generating images from text; providing temporary use of on-line non-downloadable software in the nature of an artificial intelligence model for performing generative text AI tasks and natural language processing AI tasks and for writing content based on a theme, summarizing text, document question-answering and simulating natural conversation; application service provider featuring application programming interface (API) software for performing generative text AI tasks and natural language processing AI tasks and for writing content based on a theme, summarizing text, document question-answering and simulating natural conversation; software as a service (SAAS) featuring software using artificial intelligence for performing generative text AI tasks and natural language processing AI tasks and for writing content based on a theme, summarizing text, document question-answering and simulating natural conversation; application service provider featuring application programming interface (API) software; scientific research and development; research and development services in the fields of artificial intelligence, computer science, and computer software design and development; research, design and development of computer programs and software; providing product development and engineering services in the field of artificial intelligence; providing technical research in the fields of artificial intelligence, computer science, and computer software design and development; providing consultation in the design and development of technology in the fields of artificial intelligence, computer science, and computer software design and development.
Described herein are techniques for creating graphs. A type of connection node applicable to the graphs is created in response to receiving user input. The type of connection node is configured to transmit data and not to process data. The type of connection node is configured to switch positions of input and output ports. At least one connection node of the type is added into a graph. The graph comprises a plurality of data nodes configured to process data. The graph comprises a plurality of edges connecting the plurality of data nodes. Adjustments to the graph are implemented by utilizing the at least one connection node.
According to embodiments of the disclosure, a method and apparatus for generating an effect are provided. The method includes: generating, based on a received description text, a set of interaction media elements for placement in a virtual scene; generating a code content associated with at least one interaction media element of the set of interaction media elements, the code content describing interaction logic associated with the at least one interaction media element; and creating an effect file based on at least on the code content, wherein the effect file is configured to provide an effect associated with an augmented reality scene created based on collected image data. In this way, the embodiments of the disclosure can effectively improve the efficiency of generating an effect.
Embodiment of th disclosure relates to a method, apparatus, device and storage medium for interface interaction. The method proposed herein includes: presenting an interaction interface comprising an input control for inputting a prompt; detecting whether information input in the input control comprises a target field of a predetermined type; adjusting a display style of the target field in the input control in response to the input information comprising the target field of the predetermined type; and providing auxiliary information associated with the target field in response to receiving a predetermined operation for the target field. In this way, the embodiments of the disclosure may improve the quality of an input prompt.
G06F 3/0481 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p. ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comportement ou d’aspect
G06F 3/04845 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs pour la transformation d’images, p. ex. glissement, rotation, agrandissement ou changement de couleur
29.
METHOD, APPARATUS, DEVICE AND STORAGE MEDIUM FOR MEDIA ASSET GENERATION
According to embodiments of the disclosure, a method and apparatus for media asset generation are provided. The method includes: presenting a media asset generation interface in response to a predetermined operation received in a media editing interface, the media asset generation interface comprising a canvas component; presenting, in the canvas component, a graphical content corresponding to a first interaction operation in response to the first interaction operation received via the canvas component; presenting, in a preview component of the media editing interface, a first media asset generated based on the graphical content; and adding, in response to a second interaction operation received via the media asset generation interface, a target media asset determined based on the first media asset to the media editing interface. In this way, the embodiments of the disclosure can effectively improve media asset generation efficiency.
According to embodiments of the disclosure, there are provided a method, apparatus, device and storage medium for imaging. The method includes determining a target object associated with a gaze of a user from a surrounding environment in which the user is located; determining a target depth of the target object with respect to a camera imaging the surrounding environment based on depth information of the surrounding environment with respect to the camera; and controlling focusing of the camera based on the target depth to image the target object. Thus, it is possible to focus according to the user's gazing requirement, which is advantageous to achieve a larger range of depth of field while satisfying high definition.
There are provided methods, apparatuses, devices, and media for processing video based on contrastive learning. At least one first object and at least one second object are extracted from a first frame and a second frame in a training video in training data, respectively. For a first object in the at least one first object, at least one positive sample object and at least one negative sample object associated with the first object are selected from the at least one second object based on the training data. A contrastive model is generated based on the at least one positive sample object and the at least one negative sample object, the contrastive model describing an association relationship between an object in a frame in a video and a contrastive feature of the object. The contrastive feature distinguishes whether objects in respective frames represent the same object, thereby improving the accuracy.
G06V 20/40 - ScènesÉléments spécifiques à la scène dans le contenu vidéo
G06V 10/77 - Traitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source
G06V 10/771 - Sélection de caractéristiques, p. ex. sélection des caractéristiques représentatives à partir d’un espace multidimensionnel de caractéristiques
32.
Display panel portion with an animated computer icon
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Software; downloadable computer software; downloadable computer application software; downloadable software for the analysis, evaluation, comparison and benchmarking of artificial intelligence and machine learning models; downloadable software for collecting, processing, analysing and presenting data relating to artificial intelligence and machine learning; downloadable software for evaluating the performance, capabilities, efficiency, speed, latency, cost and other characteristics of artificial intelligence and machine learning models; downloadable software for generating, displaying and comparing rankings, scores, metrics and benchmark results relating to artificial intelligence and machine learning models; Artificial intelligence and machine learning software; downloadable computer software for collecting, analyzing and organizing data in the field of deep learning; computer software, in particular for database management; downloadable computer programs and downloadable computer software using artificial intelligence for natural language processing, generation, understanding and analysis. Software engineering; design of software; development of software; software as a service [SaaS]; Platform as a service [PaaS]; Artificial intelligence as a service [AIaaS]; providing temporary use of non-downloadable software; providing an online platform for evaluating, benchmarking, comparing, analysing and testing artificial intelligence and machine learning models; providing online non-downloadable software for evaluating, benchmarking, comparing, analysing and testing artificial intelligence and machine learning models; providing online non-downloadable software for collecting, processing, analysing and presenting data relating to artificial intelligence and machine learning models; providing online non-downloadable software for evaluating the performance, capabilities, efficiency, speed, latency, cost and other characteristics of artificial intelligence and machine learning models; providing online non-downloadable software for generating, displaying and comparing rankings, scores, metrics and benchmark results relating to artificial intelligence and machine learning models; providing an online platform featuring information, data, benchmarks, rankings, evaluations and performance metrics relating to artificial intelligence and machine learning models; hosting platforms on the Internet for evaluating, benchmarking, comparing, analysing and testing artificial intelligence and machine learning models; providing artificial intelligence computer programs on data networks; technical data analysis; research and development of computer software relating to artificial intelligence and machine learning; research in the field of artificial intelligence; providing technological information relating to artificial intelligence and machine learning via an online platform.
A method for synchronizing music and animation effects in a video includes, at a computing system, automatically determining, based on one or more music beat timing parameters for a music track, a plurality of beat timestamps for a plurality of music beats, wherein the music track is selected for concurrent playback with a video track as part of an output video. Based on the plurality of beat timestamps, a plurality of animation start times are automatically determined for initiating one or more animation effects selected for playback as part of the output video. The output video is output, wherein the music track, the video track, and the one or more animation effects are synchronized such that the one or more animation effects are played at the plurality of animation start times during playback of the output video.
H04N 21/43 - Traitement de contenu ou données additionnelles, p. ex. démultiplexage de données additionnelles d'un flux vidéo numériqueOpérations élémentaires de client, p. ex. surveillance du réseau domestique ou synchronisation de l'horloge du décodeurIntergiciel de client
H04N 21/431 - Génération d'interfaces visuellesRendu de contenu ou données additionnelles
The present disclosure involves methods, apparatus, and systems for deployment to an isolated computing environment. This can include identifying a deployment request, the deployment request comprising candidate code for deployment in an isolated computing environment; performing a compliance check on the candidate code; performing an error analysis on the candidate code; identifying approved candidate code; and deploying the candidate code in the isolated computing environment.
G06F 21/53 - Contrôle des utilisateurs, des programmes ou des dispositifs de préservation de l’intégrité des plates-formes, p. ex. des processeurs, des micrologiciels ou des systèmes d’exploitation au stade de l’exécution du programme, p. ex. intégrité de la pile, débordement de tampon ou prévention d'effacement involontaire de données par exécution dans un environnement restreint, p. ex. "boîte à sable" ou machine virtuelle sécurisée
G06F 8/71 - Gestion de versions Gestion de configuration
G06F 11/3604 - Analyse de logiciel pour vérifier les propriétés des programmes
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
36.
METHOD, APPARATUS, DEVICE AND STORAGE MEDIUM FOR DATA QUERY
Embodiment of the disclosure provides method, apparatus, device and storage medium for data query. In the method, first data is obtained by a first device based on a request for data query. The request indicates a first data attribute to be classified and aggregated and at least a second data attribute and a third data attribute for classification. The first data at least includes data associated with a second data attribute. The third data fragment of a result of data query is generated based on the first data fragment of the first data and the second data fragment of the second data received from the second device. The second data at least includes data associated with the third data attribute. The third data fragment includes an element corresponding to the first data attribute classified and aggregated based on at least the second data attribute and the third data attribute.
A method, apparatus, device and storage medium for volume adjustment are provided. A method for volume adjustment includes: determining context information associated with a second media content during presentation of a first media content, the second media content being configured to be presented after the first media content; determining a processing strategy for a volume of the second media content based on at least one of the context information and reference information associated with the volume adjustment; and configuring the volume of the second media content based on the processing strategy.
This disclosure discloses a lyric file generation method and a lyric file generation apparatus, relating to the field of audio processing technology. The file generation method comprises: obtaining a phoneme propagation sequence of a song and an audio frame sequence of the song, the phoneme propagation sequence comprising a phoneme corresponding to a text unit in a lyric text of the song; determining an audio frame corresponding to the text unit in the audio frame sequence, wherein the phoneme corresponding to the text unit matches with an audio feature of the audio frames; determining time information of the text unit based on playback durations of the audio frame; and generating a lyric file of the song based on the time information of the text unit, wherein the lyric file is used to indicate a display of a text unit when the song is played to a location indicated by the time information of the text unit.
G10L 25/48 - Techniques d'analyse de la parole ou de la voix qui ne se limitent pas à un seul des groupes spécialement adaptées pour un usage particulier
G10L 15/02 - Extraction de caractéristiques pour la reconnaissance de la paroleSélection d'unités de reconnaissance
G10L 25/18 - Techniques d'analyse de la parole ou de la voix qui ne se limitent pas à un seul des groupes caractérisées par le type de paramètres extraits les paramètres extraits étant l’information spectrale de chaque sous-bande
G10L 25/24 - Techniques d'analyse de la parole ou de la voix qui ne se limitent pas à un seul des groupes caractérisées par le type de paramètres extraits les paramètres extraits étant le cepstre
G10L 25/30 - Techniques d'analyse de la parole ou de la voix qui ne se limitent pas à un seul des groupes caractérisées par la technique d’analyse utilisant des réseaux neuronaux
G10L 25/81 - Détection de la présence ou de l’absence de signaux de voix pour différencier la parole de la musique
39.
METHOD AND APPARATUS FOR VOLUME ADJUSTMENT, DEVICE, AND STORAGE MEDIUM
A method and apparatus for volume adjustment, a device, and a storage medium. The method for volume adjustment comprises: during a period in which first media content is presented, determining context information associated with second media content, the second media content being configured to be presented after the first media content; on the basis of at least one of the context information and reference information associated with volume adjustment, determining a processing policy for the volume of the second media content; and, on the basis of the processing policy, configuring the volume of the second media content. Thus, on the basis of the context information and the reference information, a volume required by a user for the next piece of media content can be predicted in advance, so that the user does not need to manually adjust the volume when watching the next piece of media content, thereby improving user experience.
The present disclosure describes techniques for implementing password resetting control. A control column comprises a variable configured to restrict an authority of a privileged user to reset passwords for owners or viewers of privacy-preserving columns. A default setting of the variable has a first value. A first instruction of granting a first user as an owner or a viewer of a first privacy-preserving column is received. A value of the variable corresponding to the first user is automatically switched from the first value to a second value in response to determining that the first user is granted as the owner or the viewer for a first time. The first value indicates that the privileged user has the authority to reset a password for the first user. The second value indicates that the privileged user lacks the authority to reset the password for the first user.
A near-eye display device, comprising a waveguide structure (10), a functional lens (20), and an adhesive structure (30); The waveguide structure (10) comprises a waveguide lens (11) and a first cover layer (12) which are stacked; the functional lens (20) is arranged on the side of the waveguide lens (11) away from the first cover layer (12); the adhesive structure (30) is arranged between the functional lens (20) and the waveguide structure (10) and comprises a adhesive layer (31) and electrode layers (32, 33) located on at least one side of the adhesive layer (31); and the adhesive layer (31) is configured to change the adhesiveness under the control of the electrode layers (32, 33).
Implementations for latent space broadening using lookalike thresholds for active learning strategies are provided. One implementation provides a computing system comprising: processing circuitry and memory storing instructions that, when executed, cause the processing circuitry to: receive a plurality of unlabeled data samples; determine a plurality of seed cases; for each of the seed cases, identify a subset of the unlabeled data samples that is semantically similar to the seed case; filter the identified subsets of the unlabeled data samples to remove data samples below a predetermined lookalike threshold, wherein the predetermined lookalike threshold describes a consistency level between an annotation and a prediction of an output of the machine learning model; annotate the filtered subsets of the unlabeled data samples to generate a labeled dataset; and train the machine learning model using the labeled dataset.
A computer-implemented method comprises a step of receiving from users respective primary entity-IDs. Each primary entity-ID comprise a first and second bit string. The method further comprises a step of generating respective mapped-IDs from each of the primary entity-IDs, such that i) each of the mapped-IDs is unique, and ii) the mapped-IDs each comprise the first bit string of the primary entity-ID and a third bit string different from the second bit string of the primary entity-ID.
The present disclosure describes techniques for implementing control over survival functions related to privacy-preserving columns. A catalog table is created to record static survival functions, each of which is related to a particular privacy-preserving column among privacy-preserving columns. Each of the privacy-preserving columns contains secret information. An output from executing each of the static survival functions does not leak secret information contained in the particular privacy-preserving column. Executions of the static survival functions are permitted for users who have no authority to view the privacy-preserving columns.
The disclosure provides a display method and apparatus and an electronic device, and the method includes: displaying a resource allocation region, the resource allocation region including at least one division line, the at least one division line dividing the resource allocation region into a plurality of sub-regions corresponding to a plurality of groups to be allocated, each sub-region including a timeline, and a plurality of sub-periods corresponding to a plurality of timelines being consecutive periods; in response to a touch operation on the at least one division line, adjusting the sub-regions corresponding to the plurality of groups to be allocated in the resource allocation region, to adjust the sub-periods corresponding to the sub-regions. The complexity of resource allocation operations is reduced.
G06F 3/04883 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] utilisant des caractéristiques spécifiques fournies par le périphérique d’entrée, p. ex. des fonctions commandées par la rotation d’une souris à deux capteurs, ou par la nature du périphérique d’entrée, p. ex. des gestes en fonction de la pression exercée enregistrée par une tablette numérique utilisant un écran tactile ou une tablette numérique, p. ex. entrée de commandes par des tracés gestuels pour l’entrée de données par calligraphie, p. ex. sous forme de gestes ou de texte
G06F 3/04886 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] utilisant des caractéristiques spécifiques fournies par le périphérique d’entrée, p. ex. des fonctions commandées par la rotation d’une souris à deux capteurs, ou par la nature du périphérique d’entrée, p. ex. des gestes en fonction de la pression exercée enregistrée par une tablette numérique utilisant un écran tactile ou une tablette numérique, p. ex. entrée de commandes par des tracés gestuels par partition en zones à commande indépendante de la surface d’affichage de l’écran tactile ou de la tablette numérique, p. ex. claviers virtuels ou menus
G06Q 10/0631 - Planification, affectation, distribution ou ordonnancement de ressources d’entreprises ou d’organisations
48.
METHOD, APPARATUS AND ELECTRONIC DEVICE FOR AUDIO PROCESSING
A method, apparatus and electronic device for audio processing are provided, and the method includes: obtaining a first vocal (S201); generating, based on the first vocal, a second vocal of one or more voice parts associated with the first vocal, a timbre of the second vocal being a predetermined timbre (S202); and playing a target audio based on the first vocal and the second vocal of the one or more voice parts, the target audio comprising the first vocal and/or the second vocal of the one or more voice parts (S203).
Disclosed in the embodiments of the present disclosure are a data processing method and apparatus, and an electronic device and a storage medium. The data processing method comprises: acquiring a first identifier of a target object entity; processing the first identifier by means of a preset function in a preset bloom filter, so as to obtain first data; and on the basis of a storage condition of the first data in a preset digit array, determining whether a subject entity executes a preset operation on the target object entity, wherein data in the preset bit array comprises: second data which is obtained by means of processing, in response to the subject entity executing the preset operation on an object entity, a second identifier of the object entity by means of the preset function.
The present disclosure relates to an interaction method, an interaction apparatus, an electronic device, a storage medium, and a program product, and in particular, to the field of artificial intelligence and computer technologies. The interaction method of the present disclosure includes: receiving first information input by a user in an interaction interface with an agent; determining, based on the first information, a target information platform matching the first information, where the target information platform includes a target multimedia resource matching demand information corresponding to the first information; and displaying the target multimedia resource in the interaction interface between the user and the agent.
Example embodiments of the present disclosure relate to a method, an electronic device, a computer readable storage medium, and a computer program product for image editing based on an editing instruction using an editing model. In the solution, a model input comprising an original image and an editing instruction may be input into a trained editing model to obtain a model output which comprises an edited image corresponding to the model input. The trained editing model is determined based on a training dataset comprising a plurality of positive and negative sample pairs, where a positive sample in a positive and negative sample pair comprises original sample data, a right instruction, and edited sample data, and a negative sample in the positive and negative sample pair comprises the original sample data, a wrong instruction, and the edited sample data.
G06T 11/60 - Édition de figures et de texteCombinaison de figures ou de texte
G06F 40/40 - Traitement ou traduction du langage naturel
G06V 10/774 - Génération d'ensembles de motifs de formationTraitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source méthodes de Bootstrap, p. ex. "bagging” ou “boosting”
53.
METHOD, APPARATUS, DEVICE, MEDIUM, AND PROGRAM PRODUCT FOR ORCHESTRATING COMPONENTS
Embodiments of the present disclosure provide a method, an apparatus, a device, a storage medium and a computer program product for orchestrating components. The method includes determining at least one defined interaction mode of a target component according to a type of a parameter of the target component. The method further includes generating an interaction mode set of the target component based on the at least one defined interaction mode, the interaction mode set supporting a plurality of combinations of streaming input, non-streaming input, streaming output and non-streaming output. The method further includes selecting a target interaction mode of the target component from the interaction mode set based on an operating environment of the target component, to orchestrate the target component.
Provided are a method and apparatus for managing a machine learning model on the basis of distillation, a device and a medium. The method comprises: using a first reference sample associated with a first reference object in an application to determine a first machine learning model, the first reference sample comprising a first reference classification for a first reference media item specified by the first reference object; using the first machine learning model to determine a prediction for a second reference classification of a second reference object in the application for a second reference media item; on the basis of the second reference object, the second reference media item and the prediction for the second reference classification, generating a second reference sample; and using the second reference sample to determine a second machine learning model, the second machine learning model describing an association relationship between objects in the application and classifications of the objects for media items. In this way, more reference samples can be obtained from sparse reference samples, thereby improving the accuracy of machine learning models while reducing interference with the normal use of applications.
A method, an apparatus, a device and a storage medium for editing content are provided. The method includes: executing, in response to an editing request received in a media editing interface, an editing operation associated with the editing request; ceasing presenting the editing interface without terminating the editing operation in response to receiving a preset operation during execution of the editing operation; presenting a reminding message associated with the editing operation in response to a completion of processing the editing operation; and presenting an editing interface in response to a trigger for the reminding message, the editing interface corresponding to an editing state after completion of the editing operation.
H04N 21/431 - Génération d'interfaces visuellesRendu de contenu ou données additionnelles
H04N 21/45 - Opérations de gestion réalisées par le client pour faciliter la réception de contenu ou l'interaction avec le contenu, ou pour l'administration des données liées à l'utilisateur final ou au dispositif client lui-même, p. ex. apprentissage des préférences d'utilisateurs pour recommander des films ou résolution de conflits d'ordonnancement
Implementations of the present disclosure relate to methods, devices, and computer program products for data augmentation. In the method, mixed data is generated from first data and second data, and the mixed data comprises a first portion from the first data and a second portion from the second data. An attention map is obtained for the mixed data based on distributions of the first and second portions in the mixed data, here the attention map describes contributions of the first and second data to the mixed data. A label is determined for the mixed data based on the attention map and a first label for the first data and a second label for the second data. With these implementations, the label is determined based on the contributions of the first and second images in an accurate and effective way, and thus has a value that is much closer to the ground true
G06V 10/77 - Traitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source
G06V 10/26 - Segmentation de formes dans le champ d’imageDécoupage ou fusion d’éléments d’image visant à établir la région de motif, p. ex. techniques de regroupementDétection d’occlusion
G06V 10/48 - Extraction de caractéristiques d’images ou de vidéos en cartographiant les valeurs caractéristiques du motif en espace paramétrique, p. ex. transformation de Hough
G06V 10/774 - Génération d'ensembles de motifs de formationTraitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source méthodes de Bootstrap, p. ex. "bagging” ou “boosting”
The present disclosure involves methods, apparatus, and systems for identifying a query to perform in an emulated data analytics environment; parsing, by a first virtual machine (VM) executing a first operating system (OS), two subsets of operations from the plurality of operations; sending, by the first VM, the second subset of operations to a custom interface; receiving, by a second VM executing a second OS and from the custom interface, the second subset of operations; executing, by the second VM, the second subset of operations using an emulated hardware accelerator executing on the second VM, wherein executing the second subset of operations comprises performing a read operation of a memory using a standard interface; and returning, by the second VM, results associated with the second subset of operations to the first VM using the custom interface.
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
58.
METHOD, APPARATUS, DEVICE, AND STORAGE MEDIUM FOR INFORMATION PROCESSING
According to embodiments of the disclosure, methods apparatuses, devices, and storage media for information processing are provided. In a method, first information input by a target object for a first processing entity is obtained, the first processing entity uniquely corresponds to the target object, based on the first information and historical interaction information between the target object and the first processing entity, and second information is generated as a reply of the first processing entity to the first information. In this way, by providing a unique corresponding processing entity for the target object (for example, a user or an organization), embodiments of the present disclosure may improve the quality of the reply generated by the processing entity.
The embodiments of the present disclosure relate to a content editing method and apparatus, a device and a storage medium. The method provided herein comprises: in response to an editing request received in a media editing interface, executing an editing operation associated with the editing request; during execution of the editing operation, in response to a received preset operation, stopping presenting the editing interface without terminating the editing operation; in response to completion of the editing operation, presenting a prompt message associated with the editing operation; and in response to triggering of the prompt message, presenting the editing interface, the editing interface corresponding to an editing state after completion of the editing operation. In this way, the embodiments of the present disclosure can save time for users and improve content editing efficiency.
The embodiment of the disclosure provides a method, an apparatus, a device and a computer readable storage medium for analyzing data. In the method, a link of a called node associated with a first node is determined, wherein a target type of data flows through the first node; data traffic on the link is obtained; and a field associated with the target type of data in the data traffic is detected, to determine a flow direction of the target type of data on the link. In this way, the target type of data can be effectively tracked from the holistic perspective.
H04L 47/2441 - Trafic caractérisé par des attributs spécifiques, p. ex. la priorité ou QoS en s'appuyant sur la classification des flux, p. ex. en utilisant des services intégrés [IntServ]
H04L 43/026 - Capture des données de surveillance en utilisant l’identification du flux
61.
METHOD, APPARATUS, DEVICE, AND MEDIUM FOR MANAGING MACHINE LEARNING MODEL
A method, a device, and a medium for managing a machine learning model are provided. A prediction of a submission event between an object and a media item provided in the application is determined using a first machine learning model, the prediction of the submission event representing a probability that the object submits a response for a question associated with the media item. Based on the prediction of the submission event, a correction weight associated with the object is determined. A reference media item and a reference question associated with the reference media item are provided to the object in the application. In response to receiving a reference response submitted by the object for the reference question, the second machine learning model is updated based on the reference response and the correction weight, the second machine learning model describing an association relationship between the object and the reference media item.
A method, a device, and a medium for managing a machine learning model based on distillation are provided. A first machine learning model is determined using a first reference sample associated with a first reference object in an application, the first reference sample including a first reference classification specified by a first reference object for a first reference media item. A prediction of a second reference classification by a second reference object in the application for the second reference media item is determined using the first machine learning model. A second reference sample is generated based on the second reference object, the second reference media item, and the prediction of the second reference classification. A second machine learning model is determined using the second reference sample, the second machine learning model describing an association between an object in the application and a classification by the object for the media item.
Provided are a method and an apparatus for managing a machine learning model, a device, and a medium. The method comprises: using a first machine learning model to determine a prediction for a submission event between a target user and a media item provided in an application, the prediction for the submission event representing the probability of the target user submitting a response to a question associated with the media item; on the basis of the prediction for the submission event, determining a correction weight associated with the target user; providing, in the application, a reference media item and a reference question associated with the reference media item to the target user; and in response to receiving a reference response submitted by the target user for the reference question, updating a second machine learning model on the basis of the reference response and the correction weight, the second machine learning model describing an association between the target user and the reference media item. Data bias in training samples can be corrected on the basis of the probability of a target user submitting a response, thereby increasing the importance of training samples corresponding to target users with low submission probabilities and improving the accuracy of the trained machine learning model.
Embodiments of the present disclosure provide a method, apparatus, device and storage medium for interaction. The method includes performing speech recognition on an audio; if a first keyword is detected in the speech recognition, presenting a first visual element having a predefined visual effect corresponding to the first keyword, the first keyword being included within a predetermined range; and if a second keyword is detected in the speech recognition, presenting a second visual element associated with the second keyword, the second keyword being not included in the predetermined range.
There are proposed methods, devices, and computer program products for extending a feature space of a data sample. In the method, a global representation is obtained for a feature in a plurality of features of the data sample. A local representation is obtained for the feature based on a classifying criterion for classifying the data sample into one of a plurality of predefined domains. A representation is generated for the feature of the data sample based on the global representation and the local representation. With these implementations, an exclusive feature space may be created for each domain identified by the classifying criterion, which is dedicated to capturing domain-specific knowledge and characteristics.
There are provided methods, devices, and computer program products for video generation. A first video is converted into a second video to change the appearance of the first video. The first video comprises a first object that performs an action and the second video comprises the same object that performs the same action. A video generating model is determined based on the first and second videos. Specifically, A first feature is determined for the first video and a second feature is determined for the second video by the video generating model. A first motion portion in the first feature is determined for the first video based on a temporal change in the first video; the second feature is updated by aligning a second motion portion in the second feature with the first motion portion; the diffusion model is updated based on the first feature and the updated second feature.
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
G06V 20/40 - ScènesÉléments spécifiques à la scène dans le contenu vidéo
G06V 40/20 - Mouvements ou comportement, p. ex. reconnaissance des gestes
A computing system for multimodal classification of video data includes processing circuitry that implements a video data classification program configured to perform classification tasks in a plurality of classification categories. In an inference phase, the processing circuitry receives video data to be classified according to a selected classification category of the plurality of classification categories and extracts a plurality of frames and corresponding text features from the video data. A classification model selection engine is implemented to select a multimodal classification model from a library of multimodal classification models based on the selected classification category. The selected multimodal classification model is queried with a prompt to classify the plurality of frames and the corresponding text features according to the selected classification category. The processor receives a prediction score from the selected multimodal classification model, indicating whether the video data includes content in the selected classification category.
G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p. ex. des objets vidéo
G06V 10/774 - Génération d'ensembles de motifs de formationTraitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source méthodes de Bootstrap, p. ex. "bagging” ou “boosting”
68.
SEARCH INTERFACE DISPLAY METHOD AND APPARATUS, ELECTRONIC DEVICE, AND STORAGE MEDIUM
The present disclosure relates to a search interface display method and apparatus, an electronic device, and a storage medium. The method comprises: displaying a search interface on a first page, the search interface providing a first search mode and a second search mode, and the search interface comprising a search input region used to input a search keyword; in the first search mode, the search interface also comprises a search prompt region, the search prompt region being used to display a means of triggering the second search mode; in the second search mode, the search input region also comprises a search category input region, the search category input region being used to input a search category; the search input region comprises a plurality of keyword input rows, and each keyword input row is used to input a search keyword.
There is a method for posting a recommendation content item. The method comprises: obtaining a plurality of posting costs corresponding to a plurality of recommendation content items, each of the plurality of posting costs indicating a cost of posting a corresponding recommendation content item at an exposure opportunity for accomplishing a first conversion event of the corresponding recommendation content item (210); determining a plurality of adjustment parameters corresponding to the plurality of recommendation content items based on values of at least one conversion metric for the plurality of recommendation content items, the at least one conversion metric being associated with accomplishing a second conversion event of the corresponding recommendation content item that follows the first conversion event (220); adjusting the plurality of posting costs based on the plurality of adjustment parameters (230); and determining, from the plurality of recommendation content items and based on the plurality of adjusted posting costs, a target recommendation content item to be posted at the exposure opportunity (240).
Methods, apparatuses, electronic devices and storage medium for service request processing are provided. User feedback data for a target service is obtained, wherein the target service is triggered based on a service request link which includes a downstream service node characterizing the target service and an upstream service node characterizing a preceding service of the target service, and the user feedback data indicates the risk of a first service request for the downstream service node; a first training sample is generated based on the user feedback data, which includes a second service request that corresponds to the first service request and is a service request for the upstream service node; and online training is performed on a target risk control model based on the first training sample to obtain an updated target risk control model, the target risk control model identifying a risky service request for the upstream service node.
Embodiments of the disclosure relate to a method, apparatus, device and computer-readable storage medium for information processing. The method includes: obtaining a first image associated with an interactive scene, the first image corresponding to a first moment; generating, with a generation model, a set of motion tokens based at least on a first image token corresponding to the first image, the set of motion tokens indicating motion information associated with a first period of time, the motion information being related to a change in the interactive scene within the first period of time; generating, with the generation model, a second image token based on the first image token and the set of motion tokens, the second image token corresponding to a predicted image of the interactive scene at a second moment; and determining, based on the first image and the predicted image, a trigger action in the interactive scene.
G06V 10/774 - Génération d'ensembles de motifs de formationTraitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source méthodes de Bootstrap, p. ex. "bagging” ou “boosting”
72.
METHOD, APPARATUS, DEVICE AND STORAGE MEDIUM FOR GENERATING MEDIA CONTENT
A method, an apparatus, an electronic device and a storage medium for generating media content are provided. The method comprises: obtaining a prompt; and processing the prompt using a media generation model, to generate media content associated with a first effect and a second effect, where the media generation model is constructedbased on: processing a training prompt using a first model associated with the first effect, to generate a first feature representation; processing the training prompt using a second model associated with the second effect, to generate a second feature representation; processing the first feature representation and the second feature representation using a discriminator to determine an adversarial loss; and adjusting, based on the adversarial loss, parameters of the first model to construct a media generation model.
Embodiments of the disclosure relate to a method, an apparatus, a device and a computer readable storage medium for information processing. The method provided herein includes: obtaining media content and user input information; and providing a segmentation result associated with an object in the media content in response to the user input information indicating a first request for segmenting the object, wherein the segmentation result is determined by a segmentation model based on the media content and a segmentation feature, and the segmentation feature is generated by a language model based on the media content and the user input information.
A method, an apparatus, a device, and a storage medium for generating an effect are provided. In a method, an interaction interface with a virtual object is presented, and the interaction interface includes a message interaction component and an effect preview component. A first message is obtained via an input control in the message interaction component, and the first message is configured to describe an effect to be generated. In response to a first effect being generated based on the first message, a second message associated with the first effect is presented in a message display area of the message interaction component, and preview content of the first effect is presented in the effect preview component.
G06F 3/04845 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs pour la transformation d’images, p. ex. glissement, rotation, agrandissement ou changement de couleur
G06F 3/0482 - Interaction avec des listes d’éléments sélectionnables, p. ex. des menus
G06F 40/166 - Édition, p. ex. insertion ou suppression
75.
METHOD OF VIDEO RESOURCE MANAGEMENT AND APPARATUS, ELECTRONIC DEVICE AND STORAGE MEDIUM
The invention provides a method and an apparatus of video resource management, electronic device and a storage medium. The method of video resource management includes: determining service metric information of each candidate video profile of a target video, to obtain at least one candidate profile combination, wherein a candidate profile combination comprises at least one candidate video profile; for each candidate profile combination, determining target metric information of a candidate profile combination according to service metric information of each candidate video profile within a candidate profile combination; determining a target profile combination of a target video from at least one candidate profile combination according to target metric information of each candidate profile combination.
H04N 21/462 - Gestion de contenu ou de données additionnelles, p. ex. création d'un guide de programmes électronique maître à partir de données reçues par Internet et d'une tête de réseau ou contrôle de la complexité d'un flux vidéo en dimensionnant la résolution ou le débit en fonction des capacités du client
H04N 21/4402 - Traitement de flux élémentaires vidéo, p. ex. raccordement d'un clip vidéo récupéré d'un stockage local avec un flux vidéo en entrée ou rendu de scènes selon des graphes de scène du flux vidéo codé impliquant des opérations de reformatage de signaux vidéo pour la redistribution domestique, le stockage ou l'affichage en temps réel
76.
METHOD AND APPARATUS FOR USING VOICE TO INTERRUPT AGENT, MEDIUM, DEVICE AND PRODUCT
A method and apparatus for using a voice to interrupt an agent, a medium, a device, and a product, relating to the technical field of voice processing. The method comprises: in the process of an agent outputting information, acquiring original information, the original information comprising at least a voice frame; extracting a feature from the original information; on the basis of the feature, obtaining a text and an interrupt prediction result, the text at least being used for the agent to determine information to be output by the agent; and, in response to the interrupt prediction result being used to represent interrupting the agent outputting information, interrupting the agent outputting information. On the basis of the feature extracted from the original information, the present disclosure obtains the text and the interrupt prediction result, that is, while performing a voice recognition task to obtain the text, synchronously determines the interrupt prediction result. Thus, in full-duplex real-time voice interaction scenarios, while generating texts in real time, the present disclosure can quickly respond to interrupt demands of users so as to improve the instantaneity of interrupts.
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for encoding data on client devices. One of the methods includes obtaining dataset for transmission; dividing the dataset into two subsets according to one or more selection criteria, wherein data items that satisfy the one or more criteria are added to a first subset and the data items that do not satisfy the one or more criteria are added to a second subset, wherein the first subset is smaller than the second subset; encoding the data items of the first subset according to a first encoding technique and encoding the data items of the second subset according to a second encoding technique; applying a local differential privacy (LDP) mechanism to data elements of the first subset and the second subset to generate an LDP message; and transmitting the LDP message to an external recipient.
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Security software; Software reliability software; Threat data detection software; Threat data analysis software; Threat monitoring sotware; Cloud network monitoring software; Real-time threat monotoring software with intuitive dashboards and customs alert; Software for scanning, detecting, removing viruses, worms, trojan horses, adware, spyware and malware; Software to protect software applications against against suspicious activity and malicious users; software for providing mobile phone security; software for providing intrusion dectection and prevention; software for data communications applications, and for the encryption and authentication of electronic information; fraud protection software; encryption software to enable secure transmission of digital information; software in the field of data security functions; application software; application software for mobile phones; computer software for controlling and managing access server applications; data processing software; software for secure storage; software for checking the security of the device and the application environment; software for optimizing applications; software for risk estimation; Virtual assistant software; Artificial intelligence software; Privacy software; Downloadable and recorded computer software for securing artificial intelligence assistants; Downloadable and recorded computer software for the secure deployment, operation and management of artificial intelligence agents; Downloadable and recorded software for protecting data privacy, preventing unauthorized access and detecting unauthorized manipulation in artificial intelligence systems. Software as a service; Software development, programming and implementation; computer programming; database design; design services relating to computer software; design services for data processing systems; design of software packages; development, design, implementation, testing, analysis and consulting services in the field of security, access, authorization, authentication, encryption and identification systems for computers, networks, mobile phones and other electronic devices; development of technologies for the protection of software applications; systems integration services; design and development of computer software for artificial intelligence systems; Administration of networks and systems; computer support services, namely, technical support and software update services; maintenance of software; surveys, advice and technical appraisals; Computer security threat analysis for protecting data; Data security services; Software as a service (SaaS) featuring software for securing artificial intelligence assistants; software as a service (SaaS) featuring software for the secure deployment, operation and management of artificial intelligence agents; platform as a service (PaaS) featuring software for the secure deployment, operation and management of artificial intelligence agents; Artificial intelligence as a service [AIaaS]; Research in the field of artificial intelligence; Platforms for artificial intelligence as software as a service [SaaS]; Software as a service [SaaS] featuring computer software platforms for artificial intelligence; Cloud computing services featuring software for cybersecurity, access control, authentication and system integrity monitoring for artificial intelligence systems.
09 - Appareils et instruments scientifiques et électriques
35 - Publicité; Affaires commerciales
38 - Services de télécommunications
41 - Éducation, divertissements, activités sportives et culturelles
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable software for providing, accessing, generating, streaming, recommending, and searching for short videos for entertainment purposes; Downloadable software for retrieving, recommending, searching, and generating multimedia content and information through voice commands; Downloadable software for analyzing, accessing, and providing AI-powered recommendations based on user profiles in the field of entertainment; Downloadable software for accessing, managing, and controlling voice-controlled communication devices; Downloadable intelligent personal assistant software for voice recognition, allowing users to search, retrieve, and receive customized recommendations in the field of in-vehicle entertainment; Recorded software for accessing, managing, and controlling voice-controlled communication devices; Recorded software for retrieving, recommending, searching, and generating multimedia content and information through voice commands; Recorded software for analyzing, accessing, and providing AI-powered recommendations based on user profiles in the field of entertainment; Computer hardware for controlling voice-controlled communication devices; Recorded software for providing, accessing, generating, streaming, recommending, and searching for short videos for entertainment purposes Business consultation; Business management; Business administration; Marketing services; Marketing research; Advertising services; Online advertising and promotional services; Rental of advertising space on in-vehicle entertainment systems; Providing consumer information services and making referrals in the field of entertainment services for products, services, events, activities, facilities and locations; Business management consulting, strategic planning and business advisory services provided to automakers in the field of in-vehicle entertainment; Providing consumer product information via social media mobile applications; Business research Streaming transmission services; Electronic, electric, and digital transmission of voice, data, images, signals, and messages; Transmission of sound, video and information; Providing voice chat services; Voice over IP services; Providing voice communication services via the Internet; Digital network telecommunications services; Providing telecommunications connections to the internet or databases; Telecommunications transmission of videocasts; Streaming of video material on the Internet; Telecommunications consultation; Leasing of telecommunications lines; Rental of telecommunications apparatus; Mobile media services in the nature of electronic transmission of entertainment media content; Video transmission over digital networks; Streaming of audio material on the Internet Video production; Video editing; Digital video, audio, and multimedia publishing services; Entertainment information; Information relating to entertainment and education provided on-line from a computer database or the internet; Entertainment services in the nature of production of in-vehicle multimedia entertainment content and distributed and provided through computer, electronic and online databases; Entertainment services in the nature of production of in-vehicle multimedia entertainment content and distributed and provided via global computer network; Providing online, non-downloadable, short-form videos in the field of in-vehicle entertainment; Providing online, non-downloadable, short-form videos in the field of pop culture, music, sports, drama, comedy, news, cartoons, and other user-generated social media content; Providing online, non-downloadable, short-form videos in the field of pop culture, music, sports, drama, comedy, news, cartoons, and other user-generated social media content via social media mobile applications; Providing online, non-downloadable, short-form videos in the field of pop culture, drama, comedy, news, cartoons, and other user-generated social media content via social media websites Mobile media services in the nature of electronic storage of entertainment media content; Intelligent voice recognition services using cloud-based software technology; Providing temporary use of on-line non-downloadable software for retrieving, recommending, searching, and generating multimedia content and information through voice commands; Providing temporary use of on-line non-downloadable software for analyzing, accessing, and providing AI-powered recommendations based on user profiles in the field of entertainment; Providing temporary use of on-line non-downloadable software for accessing, managing, and controlling voice-controlled communication devices; Software as a service (SAAS) services featuring software for providing, accessing, generating, streaming, recommending, and searching for short videos for entertainment purposes; Software as a service (SAAS) services featuring software for retrieving, recommending, searching, and generating multimedia content and information through voice commands; Software as a service (SAAS) services featuring software for analyzing, accessing, and providing AI-powered recommendations based on user profiles in the field of entertainment; Software as a service (SAAS) services featuring software for accessing, managing, and controlling voice-controlled communication devices; Artificial intelligence as a service (AIAAS) services featuring software using artificial intelligence (AI) for providing, accessing, generating, streaming, recommending, and searching for short videos for entertainment purposes; Artificial intelligence as a service (AIAAS) services featuring software using artificial intelligence (AI) for retrieving, recommending, searching, and generating multimedia content and information through voice commands; Artificial intelligence as a service (AIAAS) services featuring software using artificial intelligence (AI) for analyzing, accessing, and providing AI-powered recommendations based on user profiles in the field of entertainment; Artificial intelligence as a service (AIAAS) services featuring software using artificial intelligence (AI) for accessing, managing, and controlling voice-controlled communication devices; Providing temporary use of online non-downloadable chatbot software for simulating conversations through voice recognition, allowing users to search, retrieve, and receive customized recommendations in the field of in-vehicle entertainment; Providing temporary use of on-line non-downloadable software for providing, accessing, generating, streaming, recommending, and searching for short videos for entertainment purposes
A method, device and computer readable storage medium for reach deduplication across contents is provided. In the method, a plurality of non-overlapping object subsets is determined from an object set based on a plurality of object ranges. An object range is associated with at least one object attribute and targeted by a content of a plurality of contents that targets the object set. A reference number of objects targeted by at least one content in each object subset is determined based on a plurality of individual correlation metrics. An individual correlation metric corresponds to a content and indicates a degree of correlation between objects in the object subset and the content. A target number of objects targeted by the plurality of contents in the object set is determined based on the respective reference numbers in the plurality of object subsets.
G06F 16/00 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet
G06F 16/215 - Amélioration de la qualité des donnéesNettoyage des données, p. ex. déduplication, suppression des entrées non valides ou correction des erreurs typographiques
A computing system including one or more processing devices configured to receive a reference image and an input video. The one or more processing devices execute a video generation model to compute an output video based at least in part on the reference image and the input video. The video generation model includes a denoising diffusion model that includes self-attention layers. The video generation model further includes dynamics adapters that are respectively associated with the self-attention layers and are each configured to, for each of the input video frames of the input video, receive the reference image and the input video frame. Each of the dynamic adapters computes a self-attention guidance matrix based at least in part on the reference image and the input video frame and inputs the self-attention guidance matrix into the denoising diffusion model. The one or more processing devices output the output video for display.
Examples are disclosed that relate to promoting two-way interaction in a social media application using an interactive sticker. In one example, a social media application configured to generate a messaging graphical user interface (GUI) is executed by a sender-side computing device. An interactive sticker is displayed in the messaging GUI. A display message is sent to a receiver-side computing device. The receiver-side computing device displays the interactive sticker in a corresponding GUI based on receiving the display message. An interaction message is received from a receiver-side computing device based at least on the interactive sticker being interacted with at the receiver-side computing device. Hidden content associated with the interactive sticker is displayed in the messaging GUI based on receiving the interaction message. The receiver-side computing device displays the hidden content in the corresponding messaging GUI based on the interactive sticker being interacted with at the receiver-side computing device.
A virtual machine orchestration scheduling method, an electronic device, and a storage medium are provided. The method includes: in response to a virtual machine secondary scheduling request, creating a first virtual machine planning model according to a deployment attribute feature of an initial virtual machine deployed on a physical machine, and determining a first deployment plan that minimizes a total scheduling cost; determining an initial virtual machine to be migrated out in each type of initial virtual machine in each physical machine; creating a second virtual machine planning model for a target initial virtual machine to be migrated out with an anti-affinity constraint in the initial virtual machine to be migrated out, and determining a second deployment plan that minimizes a scheduling cost of the target initial virtual machine to be migrated out; and performing virtual machine scheduling according to the first deployment plan and the second deployment plan.
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
84.
METHOD, APPARATUS, DEVICE AND STORAGE MEDIUM FOR STICKER RESOURCE GENERATION
According to embodiments of the disclosure, a method and an apparatus for sticker resource generation are provided. A method includes: presenting an image obtaining interface associated with an application; obtaining a reference image via the image obtaining interface; and providing a second sticker resource generated by the base reference image and a first sticker resource associated with the application. The second sticker resource includes a motion associated with a target object in the reference image, and the motion is determined based on the first sticker resource.
Described are techniques for creating elements in an effect creation tool. The techniques comprises providing a naturel language string to a model, the natural language string indicating a request for creating at least one element in the effect creation tool; receiving an output string from the model, the output string corresponding to creating the at least one element; mapping the output string to at least one command supported by the effect creation tool; and creating the at least one element in the effect creation tool based on the at least one command, wherein the created at least one element is selectable via the effect creation tool for applying to a video.
The disclosure provides a system for eye tracking, comprising: at least one light source; at least one metasurface configured to receive light emitted from the at least one light source; at least one detector configured to receive light reflected by an eye of a user from the at least one metasurface and convert the received light into an electrical signal; and configured to control a reflection direction of the light from the at least one light source by the at least one metasurface to enable the reflected light to reach the at least one detector by reflection of the eye of the user. According to the embodiments of the disclosure, all solid-state beam guidance control based on the metasurfaces has the characteristics of fast scanning and wide-angle scanning, resulting in better accuracy of the beam guidance, higher consistency and reliability of the system, and smaller physical sizes.
On the basis of the embodiments of the present disclosure, provided are a content interaction method and apparatus, and a device and a computer-readable storage medium. The method comprises: presenting a viewing interface for static media content posted by a first user; on the basis of an interaction request received on the viewing interface, providing dynamic media content generated on the basis of the static media content; and in response to receiving a sending request, sending target media content in a conversation with the first user, wherein the target media content is the dynamic media content, or, the target media content is generated by means of editing the dynamic media content. Therefore, by means of the embodiments of the present disclosure, corresponding dynamic media content can be generated on the basis of static media content posted by users, such that interaction content between the users is associated with content posted by the users, thereby enriching interaction materials between the users, and improving the fun and interactivity of information interaction.
H04N 21/472 - Interface pour utilisateurs finaux pour la requête de contenu, de données additionnelles ou de servicesInterface pour utilisateurs finaux pour l'interaction avec le contenu, p. ex. pour la réservation de contenu ou la mise en place de rappels, pour la requête de notification d'événement ou pour la transformation de contenus affichés
G06F 3/048 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI]
88.
EXPRESSION RESOURCE GENERATION METHOD AND APPARATUS, DEVICE AND STORAGE MEDIUM
Provided in the embodiments of the present disclosure are an expression resource generation method and apparatus. The method comprises: presenting an image acquisition interface associated with an application; acquiring a reference image via the image acquisition interface; and providing a second expression resource generated on the basis of the reference image and a first expression resource, the first expression resource being associated with the application, the second expression resource comprising a motion associated with a target object in the reference image, and the motion being determined on the basis of the first expression resource. In this way, the embodiments of the present disclosure can generate the second expression resource on the basis of the acquired reference image and the first expression resource, thereby helping a user to better obtain desired information.
Examples are disclosed that relate to promoting two-way interaction in a social media application using an interactive sticker In one example, a social media application configured to generate a messaging graphical user interface (GUI) is executed by a sender-side computing device. An interactive sticker is displayed in the messaging GUI. A display message is sent to a receiver-side computing device. The receiver-side computing device displays the interactive sticker in a corresponding GUI based on receiving the display message. An interaction message is received from a receiver-side computing device based at least on the interactive sticker being interacted with at the receiver-side computing device. Hidden content associated with the interactive sticker is displayed in the messaging GUI based on receiving the interaction message. The receiver-side computing device displays the hidden content in the corresponding messaging GUI based on the interactive sticker being interacted with at the receiver-side computing device.
Embodiments in the disclosure provide a method, apparatus, device, storage medium, and program product for feature determination. The method includes: determining, using a visual encoder, a visual feature representation of an image, the visual feature representation having a first dimension; dividing the visual feature representation into a plurality of sub-feature representations by dimension; for each of the plurality of sub-feature representations, determining, from a codebook of a plurality of codebooks that corresponds to the sub-feature representation, a quantized feature representation that matches the sub-feature representation, each codebook including a plurality of quantized feature representations; and determining a quantized visual feature representation of the image by concatenating a plurality of quantized feature representations respectively corresponding to the plurality of sub-feature representations, the quantized visual feature representation having the first dimension.
G06V 10/46 - Descripteurs pour la forme, descripteurs liés au contour ou aux points, p. ex. transformation de caractéristiques visuelles invariante à l’échelle [SIFT] ou sacs de mots [BoW]Caractéristiques régionales saillantes
G06V 10/75 - Organisation de procédés de l’appariement, p. ex. comparaisons simultanées ou séquentielles des caractéristiques d’images ou de vidéosApproches-approximative-fine, p. ex. approches multi-échellesAppariement de motifs d’image ou de vidéoMesures de proximité dans les espaces de caractéristiques utilisant l’analyse de contexteSélection des dictionnaires
G06V 10/774 - Génération d'ensembles de motifs de formationTraitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source méthodes de Bootstrap, p. ex. "bagging” ou “boosting”
G06V 10/776 - ValidationÉvaluation des performances
G06V 20/62 - Texte, p. ex. plaques d’immatriculation, textes superposés ou légendes des images de télévision
91.
METHOD, APPARATUS, DEVICE, STORAGE MEDIUM AND PROGRAM PRODUCT FOR VISUAL GENERATION
Embodiments of the disclosure provide a method, an apparatus, a device, a storage medium, and a program product for visual generation. The method includes: generating first visual content matching the text information at a first resolution by using a trained first content generation model and based on text information; performing up-sampling for the first visual content having the first resolution to obtain up-sampled first visual content having a second resolution, where the first resolution is lower than the second resolution; and generating second visual content matching the text information at the second resolution by using a trained second content generation model and based on the up-sampled first visual content and the text information.
According to embodiments of the disclosure, a method and an apparatus for eye tracking are provided. The method comprises capturing a first image of an eye by a first camera; capturing a second image of the eye by a second camera; determining, based on information of an eye component in the first image and/or the second image, one of the first camera and the second camera as a main camera and the other one as an auxiliary camera; and controlling the main camera to operate at a power higher than that of the auxiliary camera. Therefore, the power consumption during the eye tracking may be reduced by switching between the main camera and the auxiliary camera.
H04N 23/611 - Commande des caméras ou des modules de caméras en fonction des objets reconnus les objets reconnus comprenant des parties du corps humain
G06V 40/18 - Caractéristiques de l’œil, p. ex. de l’iris
H04N 23/65 - Commande du fonctionnement de la caméra en fonction de l'alimentation électrique
H04N 23/90 - Agencement de caméras ou de modules de caméras, p. ex. de plusieurs caméras dans des studios de télévision ou des stades de sport
93.
OPTICAL MODULE, MANUFACTURING METHOD THEREOF, AND NEAR-EYE DISPLAY DEVICE
An optical module, a manufacturing method thereof, and a near-eye display device. The optical module has a light incident side and a light-exiting side, and includes a first lens, a partial reflector, a phase retarder, a second lens, a reflective polarizer, and a light-transmissive structure. The reflective polarizer has a reflective axis direction and a transmissive axis direction perpendicular to each other, the light-transmissive structure has a lowest refraction direction, a refractive index of the light-transmissive structure in the lowest refraction direction for linearly polarized light parallel to the lowest refraction direction is lowest, an included angle between the lowest refraction direction and the reflective axis direction is greater than or equal to 70 degrees and less than or equal to 90 degrees, so that the reflective polarizer has a relatively large reflective polarization selectivity ratio.
G02B 3/04 - Lentilles simples ou composées à surfaces non sphériques à surfaces continues engendrées par une rotation autour d'un axe, mais s'écartant d'une véritable sphère
A computing system including one or more processing devices configured to receive a text prompt. At a text encoder, the one or more processing devices are further configured to compute one or more text tokens based at least in part on the text prompt. At a text-to-image (T2I) generative model, the one or more processing devices are further configured to compute a plurality of latent image tokens based at least in part on the one or more text tokens. At an image decoder, the one or more processing devices are further configured to receive the latent image tokens and the one or more text tokens. The one or more processing devices are further configured to compute an output image based at least in part on the latent image tokens and the one or more text tokens. The one or more processing devices are further configured to output the output image.
A computing system is provided, including one or more processing devices configured to, during an inferencing phase, receive an input image at a dual diffusion model. The one or more processing devices are further configured to process the input image at the dual diffusion model to compute output text. The one or more processing devices are further configured to output the output text. The dual diffusion model has been computed during a training phase by finetuning a text-to-image (T2I) diffusion model, the finetuning having been performed using a finetuning dataset that includes a plurality of image-text pairs. The finetuning has further utilized a loss function that includes an image distribution loss term and a text distribution loss term.
Embodiments of the present disclosure provide a method and an apparatus for editing an audio effect, a device, and a storage medium. The method includes: creating an audio source control, an audio source controlling control, an audio control, and an audio post-processing control in an audio editing interface based on a first creation operation triggered by a user; connecting an output port of the audio source control to an input port of the audio source controlling control, connecting an output port of the audio source controlling control to an input port of the audio control, and connecting an output port of the audio control to an input port of the audio post-processing control; and controlling an original audio stream to sequentially flow from the audio source control through the audio source controlling control, the audio control, and the audio post-processing control, to obtain target effect audio.
G11B 27/031 - Montage électronique de signaux d'information analogiques numérisés, p. ex. de signaux audio, vidéo
G10L 15/22 - Procédures utilisées pendant le processus de reconnaissance de la parole, p. ex. dialogue homme-machine
G10L 21/00 - Techniques de traitement du signal de parole ou de voix pour produire un autre signal audible ou non audible, p. ex. visuel ou tactile, afin de modifier sa qualité ou son intelligibilité
97.
CONTENT GENERATION METHOD AND APPARATUS, AND DEVICE AND STORAGE MEDIUM
The embodiments of the present disclosure relate to a content generation method and apparatus, and a device and a storage medium. The method provided herein comprises: presenting an editing interface for first media content, wherein the editing interface comprises a generation entry; on the basis of a trigger for the generation entry, acquiring a generation request, wherein the generation request indicates at least one generation parameter; providing second media content in the editing interface, wherein the second media content is dynamic media content generated on the basis of the first media content and the at least one generation parameter; and in response to a posting request received in the editing interface, posting a work corresponding to the dynamic media content. In this way, by means of the embodiments of the present disclosure, dynamic media content based on first media content can be generated on the basis of a received operation. Therefore, the embodiments of the present disclosure can retain information and effects that are originally presented by the first media content and also enrich information and effects that are presented by the dynamic media content, thereby effectively improving the experience and fun of user interaction by means of dynamic effects.
G06F 16/958 - Organisation ou gestion de contenu de sites Web, p. ex. publication, conservation de pages ou liens automatiques
G06F 9/451 - Dispositions d’exécution pour interfaces utilisateur
G06F 3/0481 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p. ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comportement ou d’aspect
98.
METHOD, DEVICE AND COMPUTER PROGRAM PRODUCT FOR CONFORMATION GENERATION OPTIMIZATION
A method is proposed for conformation generation optimization. In the method, a first sample conformation of a target protein is generated by using a conformation generation model. A second sample conformation with physical information of the target protein is generated, by using a physical model, based on the first sample conformation. The physical information indicates a reference distribution of atoms in the target protein. The conformation generation model is trained with the second sample conformation.
09 - Appareils et instruments scientifiques et électriques
35 - Publicité; Affaires commerciales
38 - Services de télécommunications
41 - Éducation, divertissements, activités sportives et culturelles
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Artificial intelligence and machine learning software; Computer programmes; Display devices; Displays for vehicles; Film and video devices; Hardware and software for electronic driving assistance systems; Recorded computer software for safe vehicle driving; On-board electronic systems for providing in-vehicle entertainment; Computer programs for use in-vehicle entertainment systems; Car stereos; Communications apparatus for vehicles; On board computers for vehicles; Computer software to operate vehicles; Computer software platforms for providing, managing, recommending, searching, retrieving and playing audiovisual content, in vehicles; artificial intelligence software for content recommendation, content search, personalized content selection and user profiling; Downloadable and recorded software development tools for creating, configuring, customizing, integrating, testing and deploying in-vehicle entertainment and infotainment applications; Application development software; Software development kit [SDK]; software platforms for the development and operation of vehicle-based entertainment systems. Database management; Database management services; Computer database management services; Compilation of computer databases; Retail services in relation to computer programs for use in-vehicle entertainment systems; Wholesale services in relation to computer programs for use in-vehicle entertainment systems; advertising, marketing and promotional services provided through vehicle infotainment systems; Collection and systematisation of information into computer databases; Business consulting services relating to in-vehicle entertainment systems; Administration of businesses: Business management. Telecommunications services; Broadcasting services; Communication by computer terminals; Car telephone communications services; Mobile media services in the nature of electronic transmission of entertainment media content; Transmission of interactive entertainment software; Providing user access to computer programmes in data networks; Electronic transmission services; Electronic transmission of data, messages, images, audio, video and multimedia content; Video, audio and television streaming services; Data streaming services; Transmission of movies, videocasts, podcasts and music; Transmission and streaming of audiovisual content, including short-form video content, to vehicles; Providing access to the Internet and other communications networks; Communication services for voice-based retrieval and delivery of digital content in vehicles. Entertainment services; Interactive entertainment; Video entertainment services; Rental of recorded entertainment; Providing facilities for entertainment; Online entertainment services; Providing non-downloadable videos, films, television programs, music, podcasts and multimedia content; Publishing services; Providing online non-downloadable entertainment content via digital networks; provision of digital entertainment content through connected vehicle platforms. Software development, programming and implementation; Hosting services, software as a service, and rental of software; IT consultancy, advisory and information services; Artificial intelligence as a service [AIaaS]; Software as a service [SaaS] featuring computer software platforms for artificial intelligence; Design and development of computer software for in-vehicle entertainment systems; Rental of entertainment software; Electronic storage of entertainment media content; Providing temporary use of non-downloadable interactive entertainment software; Software as a service (SaaS) featuring software for the provision and management of in-vehicle entertainment systems; Development and hosting of software for the recommendation, retrieval and delivery of digital multimedia content; Providing temporary use of non-downloadable software featuring artificial intelligence for voice interaction, voice-controlled content search, content recommendation, content generation and user profiling; Software as a service (SaaS) featuring software for the provision, management and customization of in-vehicle entertainment systems; platform as a service (PaaS) featuring software platforms and software development tools for designing, developing, configuring and integrating in-vehicle entertainment systems and intelligent cockpit applications; cloud computing services for processing, analysing and personalising user content and interactions in vehicles.
A method for redirecting data traffic includes monitoring transmission of data traffic to a plurality of client computing devices in a geographic area via a computer network, including at least a first content delivery network (CDN) and a second CDN. A real-time Quality of Service (QoS) parameter is measured that indicates a network performance of the computer network during a current time interval. Based on the real-time QoS parameter being lower than a baseline QoS parameter that indicates a historical performance of the computer network, an incident score is calculated that quantifies a degradation in the network performance. Based on the incident score, the data traffic is automatically redirected, such that a first portion of the data traffic delivered to the plurality of client computing devices using the first CDN is reduced, and a second portion of the data traffic delivered using the second CDN is increased.
