52 results about "Visual query" patented technology

The invention belongs to the technical field of mine ventilation monitoring, and aims to solve the problems that a traditional knowledge system based on a rule base has bottlenecks in the aspects of dealing with sudden working conditions, knowledge updating and semantic reasoning, and is high in construction cost and complex to maintain. The invention provides a mine ventilation knowledge graph construction method based on a large model, and the method comprises the following steps: S100, obtaining and cleaning a multi-source heterogeneous text related to mine ventilation, and obtaining a JSON format knowledge fragment of a unified structure; s200, constructing an ontology model and defining a semantic structure; s300, constructing four types of knowledge extraction tasks, and extracting entities, attributes and relationships; s400, constructing an entity alignment module; and S500, constructing a graph database structure. According to the method, automatic structured expression, semantic consistent fusion and intelligent visual query of knowledge in the mine ventilation field can be realized, and an interpretable, extensible and reasonable intelligent support platform is provided for a mine ventilation system.

The invention discloses a traditional Chinese medicine decoction piece production data management method and system based on quality tracing, and relates to the technical field of production data management. According to the invention, a unique tracing identification code is generated for warehousing traditional Chinese medicine raw materials, and information is bound to create a digital file; in the production process, data and quality data of all procedures are collected in real time by scanning the identification codes, and a dynamic production digital file is formed; an improved TCN neural network is trained to construct a quality prediction model, and the model can accurately predict product quality by introducing optimization such as a process perception attention mechanism and parallel branches; performing real-time quality evaluation and process adjustment by using the model in production; key process data is stored through a block chain, and a traceability code is provided on a finished product package for visual query; data communication and credible tracing of a whole production chain are achieved, quality control is converted into active prediction and intervention from passive inspection, and the quality stability and management efficiency of the traditional Chinese medicine decoction pieces are remarkably improved.

The invention discloses a telemetering site position display and information query system and method based on AR information labeling. The system comprises a multi-source data management module, an interactive query module, an AR recognition module and a mobile terminal device. The interactive query module is arranged in mobile terminal equipment, and the mobile terminal equipment is in communication connection with the AR identification module through the communication module; the AR identification module is in communication connection with the multi-source data management module through the communication module; equipment pose synchronization, spatial range screening and a three-dimensional space anchoring algorithm based on ARCore are executed through the system, and finally hierarchical information capable of being interactively displayed is generated through AR label generation and rendering; the method aims at solving the problems that in the prior art, a telemetering site information query mode is backward, the information display dimension is single, and operation steps are tedious and low in efficiency, and telemetering site visual query can be achieved through the combination of the mobile intelligent device and the space positioning and AR labeling technology.

The invention discloses an NL2SQL and NL2VIS method based on large model collaborative intelligent agent, and belongs to the technical field of natural language processing. The NL2VIS method comprises the steps that candidate database modes related to natural language query are obtained from database modes, and task complexity corresponding to the natural language query is obtained according to the number of tables contained in the candidate database modes; in combination with the task complexity, natural language query is converted into a preliminary SQL query statement; verifying, repairing and feeding back the SQL query statement based on the initial SQL query statement until a final SQL query statement is generated; and converting the final SQL query statement into a visual query language. According to the method and the device, the database table, the field and the association relation of the database table and the field involved in the query intention of the user can be more accurately identified, and connection errors, field mistaken selection and information omission caused by mode misunderstanding are fundamentally reduced.

The invention relates to the technical field of data processing, and discloses a statistical report generation method and system, electronic equipment and a storage medium, and the method comprises the steps of counting a configuration request, formulating a statistical statement template, and creating a statistical task; triggering a batch processing process according to timing configuration, executing a statistical task, performing batch calculation on the source data set associated with the statistical statement template, generating a statistical result, and persistently storing the statistical result in a specified database; selecting a query mode according to the visual query request, an identifier corresponding to the statistical task and a time range selected by a user, and performing formatting and merging calculation on a query result to generate a visual data set; performing rendering calculation on the visual data set according to the visual template configuration, generating chart data and displaying the chart data; and identifying and migrating the historical statistical data, receiving a query request for the archived data through an independent query interface, and returning a corresponding result. According to the invention, diversified statistical requirements can be met, and the integrity and flexibility of data tracing are guaranteed.

The invention discloses an SAM2 small sample segmentation method based on semantic-visual dual-memory fusion, and the method comprises the steps: constructing semantic query memory, visual query memory and query-related support visual memory, and fusing the semantic query memory and the visual query memory through a memory refinement module guided by the query-related support visual memory. SAM2 dense matching and decoding module end-to-end training are combined. The problems of single memory and foreground-background confusion of an existing method are solved, target semantic consistency and fine-grained modeling ability are enhanced, segmentation precision and generalization ability are remarkably improved in a complex scene, and the method is suitable for the fields of medical image analysis, automatic driving and the like.

The application provides a kind of operation and maintenance scene visualization report generation method and system based on natural language question and answer, belongs to intelligent operation and maintenance technical field, method includes: receiving the natural language query input by user;Through the pre-training of large language model and the preset operation and maintenance terminology dictionary, the natural language query is parsed and entity is extracted, and the entity-field association table containing demand type is generated;According to demand type and semantic feature, the query type is judged to be data query or visual query;Based on the judgment result, generate structured query language sentence or visual instruction;Query is executed to the interface business database to obtain raw data;Raw data is processed and analyzed to obtain analysis result data;Call data feature adaptation algorithm to match chart type, generate and output visual report.The application realizes the full-link automation from natural language input to visual report output, reduces the operation and maintenance data interaction threshold, improves the operation and maintenance data processing efficiency and accuracy.

The invention relates to the technical field of detection and tracing based on the Internet of Things, in particular to a detection and tracing system based on the Internet of Things, which comprises a sensing layer, a network layer, a processing layer and an application layer. The sensing layer is integrated with a high-precision sensor to collect multi-dimensional data; the network layer transmits data through 5G or NB-IoT encryption; the processing layer stores and analyzes data by using a block chain and an artificial intelligence algorithm; and the application layer provides visual query and interaction functions. The system can achieve the real-time collection, reliable storage and intelligent analysis of full-chain information, overcomes the defects of an existing system in the aspects of information comprehensiveness, data safety and intelligent level, and meets the efficient, transparent and credible tracing requirements of the modern industry.

The invention relates to an infectious tophus ulcer wound nursing scheme assessment method and system, and the method comprises the steps: collecting the standardized electronic medical record data of a patient through a medical information system, including demostatistics, wound characteristics, laboratory inspection index sequences and nursing records; after structured processing, timestamp unification and missing value filling are conducted on the data, the data are input into a pre-trained deep learning model, expected wound healing probabilities, predicted healing time and complication risk scores corresponding to different nursing schemes are output, then a comprehensive assessment report is generated, the report is stored in a database, and a visual query interface is provided. And meanwhile, collecting actual nursing result data for continuous optimization and updating of the model. According to the invention, quantitative evaluation and prediction of the nursing scheme are realized, clinical decision making is effectively assisted, and the accuracy of nursing management and the resource utilization efficiency are improved.

A system may include a content repository that stores multi-modal content comprising text, visual content, and / or audio content. The system may include a processor programmed to: access a prompt comprising a text query, a visual query comprising text that describes a visual to be found, and / or an audio query comprising text that describes audio to be found, execute a language model based on the prompt to identify content from the content repository, receive, from the language model, a request for a callback function that seeks additional information to satisfy the multi-modal query, execute the callback function to obtain the additional information and provide the additional information to the language model in response to the request for the callback function, re-execute the language model based on the multi-modal query and the additional information, obtain, from the language model, content responsive to the prompt based on the additional information.

The embodiment of the invention provides a cultivated land quality monitoring-oriented data blood relationship construction and reasoning method and system, and is applied to the technical field of cultivated land quality monitoring and geographic information data management. The method comprises the following steps: acquiring multi-source heterogeneous cultivated land data of a target area, and organizing and standardizing the multi-source heterogeneous cultivated land data to generate standard cultivated land quality monitoring index data; according to the standard cultivated land quality monitoring index data, constructing a cultivated land quality evaluation system, and generating evaluation result data and consanguinity metadata; according to the evaluation result data and the blood relationship metadata, constructing a cultivated land quality blood relationship knowledge graph; and carrying out visualization processing on the cultivated land quality consanguinity knowledge graph so as to realize visual tracing and reasoning on the cultivated land quality monitoring data consanguinity. In this way, a full-link traceable blood relationship network can be constructed, and visual query and bidirectional reasoning can be realized based on the blood relationship network, so that full-link transparency and dynamic influence calculability in the evaluation process can be realized.

Systems and methods of obtaining data from a cellular network are disclosed. In some embodiments, visual query options are presented in a graphical user interface (GUI), wherein the visual query options define a query. Query option selections of the visual query options are received. A query template is generated in accordance with the query option selections. An audit of parameters is performed related with network elements of the cellular network in accordance with the query template. A report of the audit is transmitted to a user device. A visual representation of the report is presented in the GUI.

The invention discloses a development method and system of a self-adaptive registration framework. The method comprises the steps that an original image is input into a registration model and a pre-trained three-dimensional medical visual basic model VFM, the registration model is used for predicting a deformation field, and the VFM is used for extracting feature vectors and generating segmentation masks by using a double-image visual query fusion BIVQF technology; fusing the output of the encoder and the feature vector by using a hierarchical attention fusion mechanism; according to the hierarchical attention fusion mechanism, W-MCA is used in a double-flow registration network, G-CAT is used in a single-flow registration network, and features are fused. Inputting a fused result into a registration decoder for image registration; and further training the registration network by using the segmentation mask, and updating parameters of a prediction head. According to the invention, the registration efficiency can be improved.

The present application relates to a kind of petrochemical emergency rescue standard knowledge graph construction and retrieval method, including collecting petrochemical product emergency rescue standard text, and the standard text is preprocessed;Design petrochemical product emergency rescue standard ontology, according to the standard knowledge of petrochemical product related standard design petrochemical product accident rescue standard entity, petrochemical product accident rescue standard relationship and knowledge graph bottom data structure;Standard rules are used to extract entity and relationship in the standard common standard elements in entity;Based on deep learning model, the core elements of standard text are entity-recognized and relationship-extracted;The obtained petrochemical product accident rescue standard entity, triple is fused into knowledge, and is stored in graph database;According to graph database, visual query and intelligent retrieval are carried out, the present application provides a kind of petrochemical emergency rescue standard knowledge graph construction and retrieval method, integrates the standard knowledge involved in rescue and provides high-quality knowledge, provides decision information for experts and command personnel.

The application provides a density map data visual query method and device based on a flow model. The method aggregates spatio-temporal data related to a target region to obtain different data frames; based on a configured kernel density estimation algorithm, the different data frames are processed to generate density maps corresponding to the different data frames and corresponding density map data; the density map data is input into a trained flow model, the flow model encodes the density map data corresponding to any data frame to obtain an encoding result representing the density map data to a corresponding representation space; after the spatio-temporal range related to the data frame and the encoding result are associated and stored, a trained flow model is used to perform visual query on the stored data set according to a query condition input by a user, and the query result is displayed to the user. The method can significantly reduce the space occupation and can accelerate the efficiency of common aggregation operations.

A system may include a content repository that stores multi-modal content comprising text, visual content, and / or audio content. The system may access a prompt comprising a text query that describes text to be found, a visual query comprising text that describes a visual to be found, and / or an audio query comprising text that describes audio to be found, execute a language model based on the prompt to identify content from the content repository, receive, from the language model, a request for a callback function that seeks additional information to satisfy the multi-modal query, execute the callback function to obtain the additional information and provide the additional information to the language model in response to the request for the callback function, re-execute the language model based on the multi-modal query and the additional information, and obtain, from the language model, content responsive to the prompt based on the additional information.

In an example, a method for fine-tuning a Large Visual Language Model (LVLM) includes providing visual queries, each of the visual queries comprises at least an image and a textual query related to the image; processing, by the LVLM, the visual queries to extract visual embeddings from the visual queries, wherein the LVLM comprises a Visual Language Model (VLM), a first Large Language Model (LLM), and a linear projection layer interconnecting the VLM and the LLM; for visual queries: i) generating, by the LVLM, a response to the corresponding visual query based on the corresponding visual embedding; ii) evaluating, by a second LLM, the generated response to verify that the generated response satisfies predefined criteria; and iii) providing, by the second LLM, a feedback to the LVLM, in response to the evaluating the generated response; and fine-tuning the LVLM using aggregated feedback provided by the second LLM for the visual queries.

The embodiments described herein are directed to computer-implemented visual query matching methods and systems for implementing thereof. An example method includes storing first query data including queries associated with a first set of users, wherein each query includes selected criteria from multiple query criteria and first filter data for the multiple query criteria; storing second query data including metadata and queries associated with a second set of users, wherein each query includes selected

The embodiments described herein relate to a computer-implemented visual query matching method and implementation system thereof. The example method includes storing first query data, the first query data including queries associated with a first user set, wherein each query includes a selected condition from a plurality of query conditions and first filtering data for the plurality of query conditions; storing second query data, the second query data including metadata and queries associated with a second user set, wherein each query includes a selected condition from a plurality of query conditions and second filtering data for the plurality of query conditions; determining, by a processor, matching users of a first user in the first user set, the matching users being from the second user set; and providing, by the processor, a dashboard display including a matrix of the matching users to the first user.

The invention relates to the technical field of data backup and disaster recovery, in particular to an automatic backup system and method for operation and maintenance, and the system comprises file data backup, Nacos configuration backup and database table logic backup. The method has the advantages that safe and efficient remote backup storage is achieved through the SFTP, timing backup of application data, service data, logs and configuration files is supported, and a backup strategy can be flexibly configured through keyword fuzzy matching and specified name filtering. Meanwhile, the system provides an HTTP (Hyper Text Transport Protocol) interface docking short message pushing service, notifies an administrator of a backup state in real time, supports online visual query of a backup result, and greatly improves the operation and maintenance efficiency. At present, the scheme has been successfully applied in a communication system, the data loss risk is effectively reduced, manual intervention is reduced, and reliable guarantee is provided for service continuity.

The invention provides a continuous visual question and answer method, electronic equipment and a program product, and the continuous visual question and answer method comprises the steps: distributing a visual prompt subset and a question prompt subset from an initialized prompt pool for a current task; obtaining a visual query feature and a problem query feature of the current task sample; respectively retrieving a candidate visual prompt subset and a candidate question prompt subset which are most relevant to the visual query features and the question query features from the visual prompt subset and the question prompt subset; calculating the alignment loss of the input stage; calculating hierarchical consistency loss; if the prompt set of the previous task exists, calculating cross-task consistency loss; synthesizing an overall loss based on the input stage alignment loss, the hierarchical consistency loss, and the cross-task consistency loss; based on the overall loss, update cues and loss computations related learnable parameters. The reasoning consistency can be improved, knowledge forgetting is relieved, and the continuous learning ability of the model is enhanced.

This invention belongs to the field of artificial intelligence and data visualization technology, and discloses a method for processing conversational visualization intelligent agents and the intelligent agent thereof. The method includes: performing structural expansion and semantic enhancement on the acquired raw data table to generate a unified data table summary containing field type mappings and data interpretations; combining the data table summary with dialogue history to perform relevance judgment, executability checks, and solution space uniqueness analysis on user questions, classifying the questions; based on the classification results, generating a Vega-Lite specification or generating a structured text interpretation or general response by constructing and filling in a visual query language sketch; executing and rendering the generated Vega-Lite specification, generating feedback based on execution errors or semantic deviations, and driving iterative correction. This invention improves the robustness and practicality of conversational visualization systems through the collaborative design of these four steps.

The embodiment of the invention relates to an image visual unit screening method and device, equipment and a medium. The method comprises the steps that a visual unit set of a picture is extracted; obtaining a plurality of text units of a visual query text corresponding to the picture; screening out a target visual unit from the visual unit set according to the visual relevance between each visual unit and the plurality of text units until a preset screening stopping condition is met, and obtaining actual visual answers according to the screened-out target visual unit and the plurality of text units. The answer loss value of the preset standard visual answer corresponding to the visual query text is smaller than a preset loss threshold value. According to the technical scheme, on the basis that the number of the visual units is compressed, high relevance between the screened target visual unit and the visual query text is achieved, and it is guaranteed that the screened target visual unit keeps visual details related to the visual query text.

The utility model discloses a multi-bin conductive adhesive standing management device, which relates to the technical field of conductive adhesive standing and is technically characterized by comprising a placement box, a plurality of drawing guide rails are fixedly mounted at the bottom of an inner cavity of the placement box, a fixing frame is fixedly mounted at the tops of the drawing guide rails, and a tray is fixedly mounted on the fixing frame. A plurality of arc-shaped material grooves are formed in the material disc, a fixed magnet is fixedly installed at one end of the drawing guide rail, and a magnetic seat fixedly installed at the bottom of an inner cavity of the containing box is arranged on the fixed magnet. The defects that traditional conductive adhesive standing management depends on manpower, and time control is extensive are overcome. The drawing type magnetic guide rail and the independent box door are combined with an electronic lock and induction photoelectricity, so that precise positioning, environment monitoring and timed management are achieved. The operation touch screen provides visual query and work order tracing, ensures accurate execution of the process, and provides guarantee for the performance of the conductive adhesive.

Systems and methods for progressing search instances in weak signal instances can include obtaining a visual query, determining a plurality of initial search results, determining the visual query has weak search signals based on the plurality of initial search results or search intent ambiguity, generating a model-generated output to prompt the user, and providing the model-generated output for display with a subset of search results. The model-generated output can include a model-generated prompt that provides an interface for a user to provide additional inputs for additional search query clarity.

The application relates to a map, namely, a visual query system, which comprises the following function modules: a visual map screening function module, which is used for screening graph data on a map page; an edge query function module, which is used for querying according to the type of an edge; a path and snapshot saving function module, which is used for saving a current path and results in an operation path; a name display function module, which is used for setting the display type of a name; a statistical function module, which is used for statistically describing graph data; a page turning function module, which is used for turning the current graph data page; a permission management function module, which is used for managing permissions; an early warning function module, which is used for realizing the early warning function of graph data abnormality according to the hop check-off method; a label real-time dynamic function module, which is used for realizing the real-time dynamic change of a label; and a map generation time prediction function module, which is used for providing the progress estimation of map generation. Compared with the prior art, the application has the advantages of optimizing visual experience, improving abnormal early warning capability and the like.

The invention discloses an access method and device for low-code platform associated entity data. The method comprises the following steps: defining an entity association relationship based on an entity association demand and a data model specification; generating and binding a navigation column in combination with the entity metadata; field selection and navigation configuration are completed through the navigation column and the query requirement, and a visual query configuration result is obtained; converting the visual query configuration result and the entity association relationship into a query definition; constructing a navigation path structure based on the query definition, and executing query by adopting a differentiation strategy to obtain a flat query result; and performing nested structure conversion on the flat result and the navigation column to generate structured data, and accessing the associated entity data through the structured data. According to the method, the low-code complex multi-table associated query is realized, the type security is guaranteed, the N + 1 query problem is avoided, the nested structured data is automatically output, the use threshold of non-technical users is reduced, and the query efficiency and the development convenience are improved.

The invention relates to the technical field of multi-target tracking, in particular to a motion perception multi-target tracking method based on query transfer, which comprises the following steps: receiving visual target query and multi-source data stream; a combined expert decoder is adopted to process the visual query, and visual behavior characterization capable of adapting to complex motion of the target is generated; performing time sequence coding on the multi-source data stream to generate a data sequence; a time sequence consistency reward value is generated by calculating the overlapping degree of the visual residence time sequence and the data active time sequence, and reinforcement learning training is carried out on the association strategy model according to the time sequence consistency reward value; inputting the fused state space into the model to generate an association decision, and constructing a global identity trajectory; and when the target is reproduced, rebinding is executed through a multi-dimensional matching mechanism fusing appearance, motion and space prior. Through fusion of a visual trajectory and multi-source Internet of Things data and introduction of a reinforcement learning optimization long-term association strategy, accurate and long-term cross-modal target tracking in a complex farm interaction scene is realized.

A user can submit a visual query that includes one or more images. Within or in connection with the visual query, various processing techniques, such as optical character recognition (OCR) techniques, can be used to recognize text (e.g., in the image(s), around the image(s), etc.) and / or various object detection techniques (e.g., machine learning object detection models, etc.) can be used to detect objects (e.g., products, landmarks, animals, humans, etc.). Content related to the detected text or object(s) can be identified and potentially provided to the user as search results or proactive content feeds. Thus, various aspects of the present disclosure enable visual search systems to more intelligently process visual queries to provide improved search results and content feeds, including those that are more personalized and / or take into account implicit features of the visual query and / or user search intent.

The application discloses a kind of parallel visual detection method, device and electronic equipment based on large language model related to image detection technical field, the method includes: obtaining the visual feature sequence indicating image to be detected;Learnable visual query vector is constructed;Visual feature sequence and visual query vector are spliced, combined with the natural language input sequence of the target to be detected Commonly input large language model, update visual query vector, and generate the category token of target to be detected and the semantic feature representation for describing category token in self-recurrence mode;Each visual query vector is fused with semantic feature representation based on detection head, and the target feature of fusion semantic information is obtained;Target feature is processed based on the prediction branch, and multiple detection results are output in parallel.The method can complete the category identification and position positioning of multiple targets in parallel mode, improve overall detection efficiency and detection performance.