473results about "Multimedia data indexing" patented technology

The invention discloses a visual scene method, system and equipment based on digital twinning and a medium, and relates to the technical field of digital twinning and visual modeling, and the method comprises the steps: collecting multi-format source data, carrying out the field standard mapping, and carrying out the consistency verification of the multi-format source data after the field standard mapping; writing the multi-format source data after consistency verification into a to-be-fused buffer area, selecting model component data in the to-be-fused buffer area to execute coordinate reference conversion, and performing association binding on the converted model component data and the structured graphic and text information by constructing an identification field; and synchronously loading the associated and bound model component data and the structured graphic and text information to a predefined template container, generating a scene configuration file according to a container structure, and calling a release engine to register to a multi-terminal rendering service channel. According to the method, accurate alignment of multi-format model components in a unified space coordinate system is realized by constructing an affine transformation coordinate reference conversion scheme.

The invention provides an AI-based multi-user data storage docking and secure transmission method, which comprises the following steps of: acquiring a propagation path of a hot topic according to a multi-modal content association graph, performing fragmentation storage on the propagation path by adopting a clustering algorithm, and generating a fragmentation storage index table; when the relevance of different modal contents is higher than a preset threshold value, determining that the sensitivity grading result is consistent with the multi-modal relevance, performing dynamic rule adjustment by adopting a deep learning model, generating a dynamic auditing rule set, and obtaining boundary judgment parameters of the rule set; and distributing the dynamic auditing rule set and the decision transparency index to each service line by adopting a cross-platform data synchronization protocol according to the auditing decision log, generating a cross-platform consistency auditing standard, and obtaining a synchronization log of standard execution.

The invention relates to an intelligent dialogue system and method based on an AI multi-mode large model. The method comprises the following steps: collecting biological characteristic data of a user in real time; cloning a personalized expression mode of the user by using the generative adversarial network; driving the audio avatar to perform multi-round dialogue interaction with the user, capturing a real-time physiological signal of the user through an expression recognition module, and generating a dynamic response content suggestion in combination with a dialogue context; and analyzing the interaction process based on the reinforcement learning model. The multi-modal deep fusion of the voice rhythm features, the language structure features and the facial dynamic features is realized, so that the limitation of single-modal or simple feature splicing in the prior art is broken through, the emotional state of the user can be accurately and comprehensively captured, the intention is expressed and the fine physiological reaction is expressed, and the user experience is improved. And a solid foundation is laid for constructing high-fidelity user representation.

The invention discloses a digital collection full-life-cycle traceability tracking system based on a block chain, and the system comprises a digital identification module, a verification module, a packaging transfer module, a verification module, an integration module, and a system construction module, and achieves the full-life-cycle traceability tracking of a digital collection through the technologies of multi-dimensional feature extraction, watermark embedding, distributed storage, and zero-knowledge proof. And tracking and verification of the whole process from creation to transaction of the digital collections are realized. According to the system, the transaction authorization model is encapsulated by adopting the intelligent contract, so that safe transfer of ownership is ensured; a tamper-proof verification mechanism is constructed through multi-level integrity verification; different platform data are integrated by using a cross-chain technology to form a comprehensive traceability graph, so that key problems of authenticity verification, copyright protection, value evaluation and the like faced by a digital collection market are effectively solved. In addition, the system also establishes a scientific authenticity evaluation and value dynamic evaluation system, provides an objective basis for market pricing, and significantly improves the credibility and safety of the digital collections.

The invention discloses a multi-modal information identifier generation method and system based on semantic hash. The method comprises the following steps: carrying out data preprocessing and multi-modal feature extraction on multi-modal data to obtain a unified representation containing rich semantic information; mapping the features to a shared semantic space by adopting an independent alignment projection network of each mode, and introducing cross-mode contrast learning and label supervision to realize semantic alignment among different modes; compressing the high-dimensional features after multi-modal data alignment to generate a Hash code with a fixed length; generating a unified semantic hash code containing semantic information of at least two modals; searching the number of times that the Hash code appears in a database through the unified semantic Hash code, generating a redundant code, and splicing the redundant code with the unified semantic Hash code to form an identifier of the sample; on the basis of the unified semantic hash codes, the hash codes related to the to-be-queried category in the test set are queried in the training set, and unified identification and efficient retrieval of different modes are achieved.

Generative media content (e.g., generative audio) can be dynamically generated based on various inputs, which can include blockchain data. A playback device accesses blockchain data stored via a distributed ledger and generates media content based at least in part on the blockchain data. The playback device can access a library of pre-existing media segments and arrange a selection of pre-existing media segments from the library for playback according to a generative media content model and based at least in part on the blockchain data. The generated media content can then be played back via the playback device.

Generative media content (e.g., generative audio) can be dynamically generated based on various inputs, which can include blockchain data. A playback device accesses blockchain data stored via a distributed ledger and generates media content based at least in part on the blockchain data. The playback device can access a library of pre-existing media segments and arrange a selection of pre-existing media segments from the library for playback according to a generative media content model and based at least in part on the blockchain data. The generated media content can then be played back via the playback device.

Systems, methods, and computer-readable storage media for indexing a catalog of training content, and more specifically to indexing the catalog of training content using Artificial Intelligence (AI) to improve responses to queries. A system can execute a search of training course content stored in a database, identifying at least one of new training course content or updated training course content. Based on the media type of the each piece of content, the system can execute one or more data extraction algorithms, resulting in extracted data for each piece of new or updated content. The system can then add the extracted data to a semantic search index.

A computer-implemented apparatus, system, and method is disclosed for protecting sensitive data. A cognoscible computing engine is multi-layered and multi-pathed. It includes features for handling different data formats, including structured, semi-structured, and unstructured data. Features are included to support near real-time processing at scale with high accuracy. Applications include redacting or masking sensitive data to comply with data privacy and security standards.

Generative media content (e.g., generative audio) can be dynamically generated based on various inputs, which can include blockchain data. A playback device accesses blockchain data stored via a distributed ledger and generates media content based at least in part on the blockchain data. The playback device can access a library of pre-existing media segments and arrange a selection of pre-existing media segments from the library for playback according to a generative media content model and based at least in part on the blockchain data. The generated media content can then be played back via the playback device.

The invention discloses a conference content intelligent generation processing method and system based on a multi-modal large model, and the method comprises the steps: collecting the original data of a conference, and completing the standardization preprocessing; inputting a multi-modal large model, extracting multi-modal features and carrying out semantic alignment; executing cross-modal hash coding, generating binary codes and establishing an index database; performing hash retrieval on the related fragments, and constructing a conference content directed graph; based on a conference content directed graph structure, searching an optimized path by adopting a Monte Carlo tree; and generating structured conference content, and outputting a summary, an abstract and an action item. According to the method, efficient extraction, accurate retrieval and structured intelligent generation of the conference content are realized by fusing a multi-modal large model, cross-modal Hash coding and Monte Carlo tree search.

The invention discloses a multi-modality-based minority non-abandoned pattern knowledge graph construction method and system, and relates to the technical field of cultural heritage digital protection. Deep association of multi-modality knowledge is realized through a double-path entity relationship extraction mechanism, context semantics are coded by a text path by utilizing a pre-training language model, and a multi-modality knowledge graph is constructed; the method comprises the following steps: accurately extracting entities such as a pattern and an inheritor, a semantic relationship and a visual path, analyzing a pattern topological structure through a graph convolutional network, converting visual features such as lines and contours into structured relationship data, calculating cosine similarity of a text and a visual feature vector through comparative learning, establishing cross-modal mapping of the visual features and culture description, and obtaining a visual feature model; according to the mechanism, the knowledge graph simultaneously contains semantic logic and visual feature association, and construction of a complete knowledge chain from a pattern form to cultural connotation is realized.

The invention discloses a Lake and Hunan wood carving image generation method, device and equipment based on a LoRA model and a storage medium, and relates to the technical field of process digitization and image generation, and the method comprises the steps: constructing a Lake and Hunan wood carving manufacturing process feature library based on a material object scanning graph, wood texture data and a manufacturing process video of the Lake and Hunan wood carving; according to the feature library, performing hierarchical training on the initial LoRA model according to a texture layer-cutter layer-pattern layer hierarchical logic to obtain a hierarchical LoRA model, and performing hierarchical fusion on the hierarchical LoRA model and a potential diffusion model to form a lake and Hunan woodcarving image generation model; and analyzing text cue words input by a user by using a keyword system in the feature library, extracting wood carving types, timber texture parameters, folk pattern requirements and scene adaptation features, and inputting the features into the lake and Hunan wood carving image generation model to obtain a target lake and Hunan wood carving image. According to the method, the lake and Hunan woodcarving image with the process reduction degree and the scene adaptability can be generated.

Generative media content (e.g., generative audio) can be dynamically generated based on various inputs, which can include blockchain data. A playback device accesses blockchain data stored via a distributed ledger and generates media content based at least in part on the blockchain data. The playback device can access a library of pre-existing media segments and arrange a selection of pre-existing media segments from the library for playback according to a generative media content model and based at least in part on the blockchain data. The generated media content can then be played back via the playback device.

Embodiments of the present disclosure provide a method, apparatus, electronic device, and storage medium for collecting media content. The method includes: in response to a collection operation on media content, adding the media content to the media content collection list of the current user, and displaying a favorites list of the current user, where the favorites list is used to display first identifiers of at least some of the current user's favorites; in response to a trigger operation on the first identifier, adding the media content to the favorite corresponding to the first identifier on which the trigger operation acts. By adopting the above technical solutions, the embodiments of the present disclosure can enrich the collection methods of media content.

The invention discloses a video storage and retrieval method, device and equipment based on a B + tree, and relates to the field of data processing. In the method, a video data stream is divided into a plurality of preset space grids; recognizing a dynamic target which continuously moves in the video data stream; determining a target space grid where the dynamic target is located, and generating a spatio-temporal trajectory fragment; constructing a B + tree index structure; receiving a retrieval request, and executing range query by using the B + tree index structure and the compound key to obtain a candidate fragment set; traversing the target spatio-temporal trajectory fragments in the candidate fragment set, determining a corresponding target identifier based on the query dynamic target, and accumulating all overlapping durations generated by the query dynamic target to obtain a total effective stay duration; and screening out the query dynamic targets of which the total effective staying duration is greater than or equal to a preset duration threshold value, and outputting the query dynamic targets as a final retrieval result. By implementing the technical scheme provided by the invention, the retrieval efficiency of the video data is improved.

The invention discloses an intelligent retrieval method and system for association of an image and content in a PDF document, and relates to the technical field of data process.The method comprises the steps that a document preprocessing strategy is called to preprocess the PDF document, and an image processing result and a content processing result are obtained; performing association analysis on the image processing result and the content processing result according to an association index mechanism to obtain an image-text index structure; and performing retrieval matching on the target retrieval request of the PDF document by taking the image-text index structure as a benchmark to obtain target retrieval information. According to the method, the technical problem that the retrieval efficiency and accuracy are insufficient due to the fact that an existing PDF document retrieval method cannot effectively associate the image and the text content is solved, and the technical effects that intelligent associated retrieval of the image and the text content is achieved by constructing the image-text index structure, and the retrieval efficiency and accuracy are improved are achieved.

Systems, methods, and computer-readable storage media for using distinct Artificial Intelligence algorithms to review incident reports and identify, within a corpus of training courses, which courses would be best for mitigating or preventing future incidents. A system can receive an incident record involving an individual human being involved in an incident, then analyze that incident record by executing a first Artificial Intelligence (AI) algorithm, resulting in a natural language incident summary. The system can then generate, by executing a second AI algorithm using the natural language incident summary, corrective training recommendations for the individual human being, the corrective training recommendations predicted to perform at least one of mitigating or preventing the incident from occurring again, and provide those corrective training recommendations to an authority over the individual human being.

The present disclosure provides a network model training method, a data processing method, and an apparatus. The network model training method comprises: acquiring target sample data, wherein the target sample data comprises text sample data and image sample data; inputting the target sample data into a network model to be trained to obtain a sample recognition result; and adjusting a parameter of a text encoder on the basis of a text recognition result and first supervision data corresponding to the text recognition result, adjusting a parameter of an image encoder on the basis of an image recognition result and second supervision data corresponding to the image recognition result, and a hybrid image-text recognition result and third supervision data corresponding to the hybrid image-text recognition result, and adjusting a parameter of a hybrid encoder on the basis of the hybrid image-text recognition result and the third supervision data corresponding to the hybrid image-text recognition result to obtain the trained network model formed by the text encoder, the image encoder, and the hybrid encoder.

A system and method for media content management include creating, via a digital vault, a container file comprising media content submitted by a first user and content metadata; verifying, via the digital vault, a completeness of the content metadata associated with the media content in the container file; classifying, via the digital vault, the container file based on the completeness of the media content; capturing, via the digital vault, event metadata when a second user gains access to the container file, the event metadata comprising at least one of identification of the second user, an activation timestamp, a duration of access, portions of the container file accessed, and changes to the container file; and enabling a private communication channel between parties affiliated with the media content to permit messaging among the parties affiliated with the media content via the private communication channel.

The invention relates to a multi-dimensional knowledge base construction and query method based on a multi-modal large model, and belongs to the technical field of AI large model application. The method comprises the following steps of: analyzing a text file containing text, table and picture contents; selecting a pre-trained large language model and a multi-modal large model, generating text abstracts and picture abstracts by utilizing the models, and enabling storage paths of the picture abstracts to correspond to storage paths of pictures one by one; selecting a text embedding model to construct a vector database and a retriever; and constructing a retrieval chain based on the multi-modal large model. According to the method, construction from a single text knowledge base to a multi-dimensional knowledge base is achieved, a multi-dimensional information retrieval method is provided, the problem of construction of the multi-dimensional knowledge base based on the vectorization technology is solved to a certain extent, and the large model output quality based on the retrieval enhancement generation technology is remarkably improved.

The invention discloses a digital media content element accurate screening method based on artificial intelligence image recognition, and relates to the technical field of digital media, and the method comprises the steps: building a distributed capture network to form a dynamic content pool, and building a metadata index database; calling a multi-modal image perception engine to generate a double-layer characteristic spectrum containing dominant and recessive elements; constructing a distributed recognition model cluster based on federated learning; converting the user demand into a screening parameter set and generating a decision tree; screening and secondarily verifying an output result through a double-path matching mechanism; and constructing a reinforcement learning reward function based on user behaviors, and driving the model and the decision tree to co-evolve. Multi-source heterogeneous content full-dimension analysis is achieved, the recognition comprehensiveness and depth are improved, knowledge barriers and privacy risks are solved, the screening accuracy and flexibility are improved, the system is endowed with the continuous optimization capacity, and the method is suitable for efficient and accurate digital media content screening scenes.

Systems and immersive methods are provided for aggregation and organization of image, video and digital rights data. In an exemplary embodiment, a system and method for aggregation and organization of media data acquired from a plurality of sources is provided. The system and method include a data collection element, a brand commercial (POPmercial) placement for sponsorship element, a stake and mining rewards (Futures In Popular) against placed media element and a user interface that allows publishing of a unique curated media stream as a first-time-ever NFT BROADCAST, (POPcast).

Systems and methods directed to a service that analyzes media and outputs a confidence score of the media based on inconsistencies within media and differences between source media and the media, are described herein. In one aspect, a media file may be obtained at a computing resource service provider. The media file may be analyzed using at least one of a plurality of functions to generate media results that indicate inconsistencies within the media file, and / or differences between the media file and corresponding media registered with the computing resource service provider or contextual media that contains similar content to the media file, where individual functions of the plurality of functions are executed in parallel by at least one compute unit. A confidence score, which indicates a significance of the inconsistencies within the media file and / or differences from the registered or contextual media, may be generated based on the media results.

The invention belongs to the field of medical data processing. The invention provides a multi-modal data verification system and method in medical scientific research. The method comprises the following steps: extracting multi-modal data from different storage media; respectively analyzing and processing the extracted multi-modal data, respectively establishing a feature data model of each modal data and establishing a feature index; mapping the feature data models of the modal data to a unified vector space, performing data fusion according to the relationship of feature indexes of the feature data models, and generating and storing a wide model with multi-dimensional indexes; and according to a verification rule in a data processing process, slicing the wide model according to the feature index, and extracting a data feature information part corresponding to the verification rule to complete data verification. The method has the beneficial effects that all data of different modalities are subjected to homogenized fusion, so that verification for data of the same modality is not needed any more, and the verification result is more accurate.

The invention discloses a cross-modal conference information association retrieval method and system and a medium, and relates to the technical field of artificial intelligence, and the method comprises the following steps: carrying out feature extraction on obtained multi-source heterogeneous data to obtain multi-modal features, and uniformly mapping the multi-modal features to a first feature space of a preset dimension; in the first feature space, cross-modal deep fusion processing is performed on the multi-modal features, and a joint embedding space with consistent semantics is constructed according to the cross-modal deep fusion processing; constructing a vector index database based on a multi-modal feature vector in the joint embedding space, receiving a natural language query and mapping the natural language query to the joint embedding space, executing two-stage retrieval, and then obtaining a semantic fusion score based on calculated semantic fusion scores; multiplying a time sequence reward value based on the query time deviation and a dynamic reward value based on the core word matching degree to obtain a dynamic fusion score, and performing fusion sorting on the candidate set to obtain a final sorting result and an associated retrieval result; according to the method, refined sorting of the retrieval results is realized.

The invention discloses a task processing method and an intelligent device, and relates to the technical field of intelligent devices, and the method comprises the steps: obtaining multi-modal data which comprises task information of a to-be-processed task in a real-time interaction scene of a physical entity and an environment; performing feature extraction and feature alignment processing on different modal data in the multi-modal data to obtain a first feature after feature alignment; performing cross-modal data retrieval on a knowledge base based on the first feature to obtain target retrieval data; performing feature fusion on different modal data features in the first features to obtain second features; and making a decision based on the target retrieval data and the second feature by using a decision model to obtain an action instruction sequence, and executing the to-be-processed task based on the action instruction sequence.

The invention discloses a multi-modal data quality evaluation method based on deep learning. The method comprises the steps of obtaining first modal record data and second modal record data which are marked to be aligned in a database; respectively carrying out semantic feature extraction on the first modal record data and the second modal record data to obtain a text structured data semantic coding feature tensor and a metadata description semantic coding feature vector; performing cross-modal joint coding on the text structured data semantic coding feature tensor and the metadata description semantic coding feature vector to obtain a structured-metadata cross-modal quality evaluation joint coding feature tensor; generating reconstruction record data based on the structured-metadata cross-modal quality evaluation joint coding feature tensor, and calculating offset features of the reconstruction record data; performing quality evaluation on the offset features through a first deep learning model; according to the method, through semantic coding feature extraction, fine-grained hash cross-modal coding and bidirectional reconstruction offset evaluation, the accuracy of data quality evaluation is improved.

The invention relates to the technical field of digital asset management analysis, in particular to a digital asset intelligent analysis platform based on a block chain intelligent contract technology. The computing power resource state coupling module is used for obtaining the saturation degree of computing resources by capturing information of a task control block and combining the load rate of a processor, and embedding and collecting mapping data streams to generate a management and control data packet; the abnormal data screening module is used for executing local serial processing when the saturation degree of the computing resources is lower than an I / O throughput threshold value, and otherwise, hardware acceleration is carried out, and a to-be-verified digital sequence is constructed; generating an abrupt change collection feature vector based on the to-be-verified digital sequence; and the component resume anchoring module is used for carrying out data binding operation on the abrupt change collection feature vector, generating a single-piece digital traceability certificate, carrying out aggregation compression, obtaining a batch verification root value and outputting a quality signal digital right. According to the method, a load awareness and distributed storage partitioning strategy is constructed through indexes, and the I / O frequency and transmission bandwidth occupation of whole library retrieval are reduced.