463results about "Vectoral format still image data" patented technology

The invention discloses a transformer substation engineering construction drawing intelligent analysis and evaluation system based on image recognition, and relates to the technical field of transformer substation engineering construction informatization. The data processing center is in communication connection with a data acquisition layer, an image preprocessing layer, a feature extraction layer, an intelligent analysis layer, an evaluation decision-making layer and an application display layer, and all layers of architectures are in electric signal connection. According to the method, the improved convolutional neural network model is adopted, and an image preprocessing algorithm specially aiming at engineering drawing feature optimization is combined, so that the drawing recognition accuracy is remarkably improved compared with a traditional OCR technology, the manual proofreading workload is greatly reduced, a drawing element correlation analysis system based on a knowledge graph is constructed, and the engineering drawing recognition accuracy is improved. Key information such as equipment arrangement, line connection and size marking in the drawing can be automatically extracted and associated, and structural storage and intelligent retrieval of drawing content are achieved.

The invention relates to the technical field of Otwei interactive maps, and discloses a geological data interaction method and system based on an Otwei interactive map. The method comprises the following steps: carrying out feature recognition and structural analysis on original geological data to obtain a standardized data packet, and establishing a geographic space reference conversion index table; performing feature extraction and classification on geological elements in the standardized data packet to obtain structured geological data; importing the structured geological data into an Ovoucher interactive map, and carrying out local registration through a mesh generation technology to obtain a visual geological element map layer; geological element drawing and attribute input are carried out, and an edited geological data set is obtained; and carrying out structure recombination and reverse coordinate conversion to obtain a standard format data file adaptive to the target geological information system. According to the method, accurate conversion of multi-source geological data between different coordinate systems and measuring scales is realized, and the problem of spatial dislocation during integration of different-source geological data in a traditional method is effectively solved.

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.

A method for managing a framework includes: receiving, by a GUI, a query that is sent to a first module; analyzing, by the first module, the query to infer intention; making, by the first module, a determination that the intention is not searching for an object in a database; sending, by the first module, the query to a second module; transforming, by the second module, the query into a vector that is sent to a third module; performing, by the third module and using the vector, a search for a nearest image in the database; identifying, by the third module, a path associated with the nearest image, which is sent to an analyzer, in which the analyzer further sends the path to a fourth module; and fetching, by the fourth module and based on the path, an image from a store, which is sent to the GUI.

The invention relates to the technical field of machine vision, and discloses a surveying and mapping geographic information analysis method and system based on machine vision and a medium. The method comprises the following steps: preprocessing multi-source remote sensing data to obtain a standardized surveying and mapping data set, and extracting ground feature edge and texture information to obtain a multi-scale spatial feature and a semantic segmentation result; carrying out multi-source data integration to obtain a unified geographic element representation diagram, and carrying out geographic element identification on the unified geographic element representation diagram to obtain a surveying and mapping geographic element set; performing Bayesian inference of spatial uncertainty quantization and parameter uncertainty quantization on the surveying and mapping geographic element set to obtain a comprehensive uncertainty evaluation result; and constructing vectorized geographic information based on the surveying and mapping geographic element set and the comprehensive uncertainty evaluation result. According to the method and the device, the edge information of the geographic elements is effectively reserved, the identification precision of the geographic elements is improved, the geographic information expression is more structured, and automatic updating is realized.

Described is a system for identity fraud detection by receiving an image of a user for an identity verification process of the user; generating a vector embedding for a face within the image using a machine learning model, comparing the vector embedding with at least two embedding repositories to determine a likelihood of fraud by: comparing the vector embedding with a first index of embeddings, the first index being updated at a first time interval; comparing the vector embedding with a second index of embeddings, the second index being updated at a second time interval, the first index and second index having at least a subset of the same points in the multidimensional space; and determining a characteristic of potential fraud based on the comparison of the vector embeddings with the first index and second index; and outputting an identity verification result based on the likelihood of fraud.

Provided are a map updating method and apparatus, a model training method and apparatus, an electronic device, and a medium, relating to the technical field of artificial intelligence, and in particular to the fields such as automatic driving, intelligent traffic, computer vision, and image processing. A specific implementation solution is: for a same piece of position information, determining associated historical map data and M pieces of collected image data based on a time sequence, wherein M is an integer greater than or equal to 1; respectively encoding the historical map data and the M pieces of collected image data to obtain a historical map feature and M collected image features; determining position information and category information of a target instance on the basis of the historical map feature and the M collected image features, wherein the target instance represents lane information; and updating the map data on the basis of the position information and the category information of the target instance.

The invention relates to the technical field of geographic information processing, in particular to a geographic surveying and mapping method and system based on an unmanned aerial vehicle, and the method comprises the following steps: obtaining surveying and mapping point cloud data and aerial survey vectorization boundary data of the unmanned aerial vehicle, calculating a spatial distance, screening adjacent points, and constructing a topological adjacent point set. According to the method, construction of a topological adjacent point set is optimized through spatial screening of surveying and mapping point cloud data and vectorized boundary data, data redundancy is reduced, the structural rationality of surveying and mapping results is improved, abnormal data is screened through combination of projection difference analysis and point cloud density, and accurate recognition of conflict areas is achieved. Shortest path calculation optimizes connection of conflict points and boundary points, reduces path redundancy, improves spatial consistency of surveying and mapping data, fits error screening to adjust the boundary points, enhances stability of surveying and mapping boundaries, and combines closure calculation with topological weight optimization to improve integrity of regional surveying and mapping and boundary connection quality. And the surveying and mapping result is more standard in the aspects of spatial distribution and connectivity.

Image similarity search results can be improved by augmenting a query image with images that are generated based on the query image. The generated images can have different camera poses, different lighting conditions, etc. The generated images can be generated using machine learning models. Using an ensemble of images having the query image and the generated images when searching a library of candidate images can improve performance of image similarity search. Producing effective generated images is not trivial. Also, an image similarity search algorithm may be modified to identify and rank top matching images that are most similar to the ensemble of images.

Embodiments of the present disclosure relate to multimodal AI-based search for digital assets via an indexing and / or search pipeline. With respect to the indexing pipeline, some embodiments obtain first data and second data associated with a first digital asset. Such data represents different data types or modalities of the same digital asset. After obtaining the first and second data, some embodiments then generate a composite index. After the composite index is built such index can then be used to execute a query via the search pipeline. To execute the query some embodiments compute a relevance score for each digital asset, of multiple digital assets, based at least in part on a measure in which each digital asset satisfies one or more parameters or conditions for two or more data types of the query. Various embodiments then rank each digital asset and present one or more associated indicators.

The invention discloses an intelligent flight route planning method and system for a low-altitude logistics aircraft, and the method comprises the steps: obtaining the three-dimensional space map data of the current position of the aircraft, including the coordinate information of a building and a telegraph pole, and the boundary range of a no-fly zone; acquiring wind speed, wind direction and rainfall data of the current area from a meteorological data source, and calculating meteorological impact factors by combining aircraft performance parameters; dynamically adjusting the candidate flight routes according to the maneuvering characteristic parameters of the aircraft, and calculating the flight time, the energy consumption cost and the safety risk score of each route; meteorological changes in the flight process are monitored in real time, and if the meteorological conditions exceed a preset threshold value, the meteorological data are obtained again, and the meteorological influence factors are updated; and carrying out local optimization adjustment on the current flight route according to the updated meteorological influence factor, generating a new flight route segment and replacing the original segment.

The present disclosure provides a method, a device, and a product for retrieval. The method includes acquiring context information related to an image and determining a representation of the image based on image data and the context information of the image, where the context information includes at least one of environment parameters, user behavior data, time elements, or field metadata. The method further includes encoding the representation as an image vector in a high-dimensional vector space and storing it into an image vector database. When retrieval is performed, a query that includes text information and that is for the image vector database is received, and an image associated with the text information is determined from the image vector database. The method according to the present disclosure can improve accuracy and efficiency for image retrieval.

The invention discloses a data container storage and management method based on a multi-scale space subdivision grid, and the method comprises the steps: constructing a multi-scale space subdivision grid coding system covering the earth surface and the height dimension based on an earth space subdivision theory, and endowing each grid with a unique code to form a unified space-time framework; multi-source data of images, vectors, non-space and the like are collected and transmitted to a processing center, and after consistency detection and normalization processing are carried out, unified grid codes are generated for various kinds of data based on the coding system, and mapping is established; and finally, storing the coded data into a database, updating an index, realizing dynamic scheduling, logic aggregation and visual display of multi-source data by means of unified coding, realizing efficient management and control and cross-domain collaboration of massive heterogeneous data, and improving data storage consistency and retrieval and display efficiency. According to the method, the problems of fragmentation of spatial big data, slow retrieval response, difficulty in cross-domain fusion and the like are effectively solved, and the management efficiency and the sharing depth of the spatial data are remarkably improved.

A system and a method are disclosed for classifying features from an input image. The method includes generating, by a processing circuit, a segment feature from a first input image, the segment feature corresponding to a group of pixels associated with an object represented in the first input image, and being an out-of-vocabulary segment feature; performing, by the processing circuit, a retrieval of a first feature vector, corresponding to the segment feature, from a database of feature vectors, the first feature vector representing an object-specific segmentation mask; and generating, by the processing circuit, an output segmentation mask based on the first feature vector.

A method of clustering patterns of an integrated circuit includes; providing a pattern image and numeric data, as input data corresponding to a first pattern to a first model, wherein the first model is trained by a plurality of sample images and a plurality of sample values, obtaining a content latent variable using the first model, and grouping a plurality of content latent variables corresponding to a plurality of patterns into a plurality of clusters based on a Euclidean distance, wherein the numeric data represents at least one attribute of the first pattern.

The invention discloses a visual question-answering system based on multi-modal knowledge autonomous learning and a construction method, and belongs to the technical field of artificial intelligence. The invention provides a visual question and answer model construction method fusing image information, natural language questions and external knowledge. A knowledge dynamic screening and replacement strategy is constructed by introducing an autonomous evolution mechanism, and whether knowledge is inserted or updated can be judged according to a current training state and knowledge similarity, so that the problem that a traditional static knowledge base cannot adapt to task changes is solved. According to the method, through pseudo data construction and multi-modal triple extraction, structured and high-association-degree'image-question-answer 'knowledge representation is established, so that knowledge has better semantic expression ability, and redundancy and noise are effectively reduced. According to the method, rapid retrieval and active calling of knowledge are achieved by means of the vector indexing technology, key support information can still be obtained in a complex scene, and the expression of the model in a visual question-answer task based on knowledge is remarkably improved.

The invention discloses a power grid GIS data editing method and system, electronic equipment and a storage medium. The method comprises the steps that a server constructs power grid vector slice data based on power grid GIS data and converts power grid equipment data into GeoJSON data; the client obtains and loads the vector slices, picks up a power grid graph from the vector slices according to the position of the edited equipment, adsorbs the power grid graph to the edited equipment, and requests the server for GeoJSON data of the corresponding equipment; the server performs query based on the edited device to obtain a device associated with the edited device, and sends GeoJSON data of the edited device and the associated device to the client; and the client establishes a relation with the GeoJSON data according to a pre-configured vector slice layer, captures an editing operation, superposes the vector slice and the GeoJSON data and then displays the superposed vector slice and GeoJSON data in real time. The problems of graph rendering and large data volume online editing are solved by using a data layering mechanism combining vector slicing and GeoJSON, and the rendering efficiency is improved.

The invention discloses a perspective analysis method and system based on multi-element space superposition, and belongs to the technical field of geographic information processing.The perspective analysis method comprises the steps that analysis range data input by a user is obtained, and the analysis range data is generated through map drawing or external vector file import; selecting at least two analysis object layers; performing spatial alignment, coordinate system conversion and attribute field standardization processing on the analysis range data and the analysis object layer; a parallel spatial indexing technology is adopted, all analysis object layers and analysis range data are superposed at a time, and a fine-divided result library is generated; storing a space unit ID and an original layer attribute field in the fine crushing result library; calculating a target field value according to the area proportion of the space unit based on a preset adjustment rule, and outputting the target field value to the space data file and the table file; generating a multi-dimensional statistical report according to user-defined dimensions and statistical indexes through a perspective analysis engine on the basis of the fine crushing result library; and outputting the fine space data file and the analysis report according to the filtering condition.

The invention belongs to the field of large models, and particularly relates to a document question and answer method and system based on multi-modal primitives, a terminal and a medium, and the method comprises the steps: extracting title primitives, paragraph primitives, image primitives and table primitives of a plurality of documents uploaded by a user; constructing a correlation mapping table of the paragraph primitives, the image primitives and the table primitives; converting the primitives of the text modality into text vectors for storage; converting the user question into a query vector; screening out a target title primitive and a target paragraph primitive according to the query vector, and obtaining a related target image primitive and a target table primitive; and constructing the target title primitive, the target paragraph primitive, the target image primitive, the target table primitive and the user question into a cue word, inputting the cue word into a multi-modal large language model for processing, and outputting a question result. Question answering is carried out based on the multi-modal information, and the accuracy and interpretability of the question result output by the model are improved.

Disclosed is a mutually generative artificial intelligence system based on multi-dimensional spatiotemporal information vector graphics, relating to the field of artificial intelligence and engineering applications. Based on a geographic information system (GIS) or a computer-aided design (CAD) platform and a data source, a multi-dimensional vector spatiotemporal large model terminal, a multi-dimensional spatiotemporal information processing agent terminal, and an intelligent information system application terminal are constructed. For multi-dimensional spatiotemporal data such as two-dimensional and three-dimensional vectors and temporal states, a multimodal spatiotemporal large model having an understanding capacity for an engineering professional knowledge system, a data processing flow, multi-dimensional vector graphics, and thematic graphics-text documents is pre-trained to achieve the mutual expression and generation of engineering multi-dimensional vector graphics and thematic graphics-text documents and to form an intelligent engineering graphic data processing application.

The invention discloses an agricultural insurance data acquisition and management system based on satellite remote sensing. The system comprises a data acquisition module, a preprocessing module, a verification module and a management module. The data acquisition module covers basic, universal and vector data acquisition according to data types; the preprocessing module improves the quality of collected data; the verification module verifies a cultivated land vector and insured user information, and data accuracy and reliability are enhanced; the management module builds two libraries, and constructs an agricultural insurance data large model by utilizing knowledge graph modeling. In the technical application, on the basis of satellite remote sensing and A I, large-user plot data is collected by means of an image segmentation algorithm, and the cost is reduced. A full-coverage model is constructed through abstract materialization, and business application is supported. Technical means such as satellite remote sensing, weight dispatch data superposition and AI image recognition are used for verifying data, manual operation is reduced, verification accuracy is guaranteed, data value is mined, and the agricultural insurance data management level is improved.

The disclosure relates to systems and methods automatically extracting an image and related image components, computationally determining an understanding of the image, and generating mathematical vector embeddings via sentence encoders based on the computationally determined understanding. The mathematical vector embeddings may be used for semantic image retrieval that enables image searching based on a semantic understanding of input images and / or input text. The mathematical vector embeddings may be used for training and executing generative Artificial Intelligence (AI) models to create new content that includes retrieved images and / or generate new images.

The invention relates to the technical field of geographic information systems, in particular to an incomplete road network repairing and reconstructing method based on AI recognition. Comprising the following steps: S1, road surface data geometric restoration and road width calculation; s2, reconstructing a target road network topology; s3, road attribute matching; and S4, topology simplification and output. According to the method, through the dynamic distance threshold value and topology verification, broken roads are intelligently connected, the disconnection phenomenon is eliminated, a topology connected road network is constructed, and a reliable data basis is provided for path planning. The width is calculated through correlation between the road surface and the center line, and the external road network attributes are fused, so that the output road network has key information such as the road width and grade, and the trafficability evaluation requirement in mechanical construction is met.

The invention relates to the technical field of computer information retrieval, and discloses a security person and vehicle multi-mode retrieval method and device, electronic equipment and a storage medium, and the method comprises the following steps: arranging various sensor equipment in a security area; uploading the collected video and image to a cloud object for storage; performing image text feature extraction by using the large model; receiving an image or text request uploaded by a user, calling the corresponding large model to carry out image text feature extraction, and carrying out feature retrieval through the vector database; an Elasticsearch database is used for further query, screening item information set by a user is combined, and the device comprises a data acquisition module, a management platform service module, a data storage module, a large model feature extraction module and a feature retrieval and matching module. According to the method, a clock callback detection and compensation mechanism, machine ID unified configuration and microsecond-level timestamp serial number generation are introduced, so that the technical effect of avoiding ID conflicts and time sequence errors is effectively achieved.

The invention relates to the technical field of channel monitoring and underwater topography analysis, in particular to a multi-beam sounding data driven underwater topography profile extraction method and device and a medium, and the method comprises the steps: obtaining channel region multi-beam sounding original data, carrying out the standardized preprocessing, and outputting a sounding data set; performing spatial interpolation and vectorization processing on the sounding data set to generate channel geological data, and issuing the channel geological data as a similar three-dimensional channel bottom graph through a geographic information service platform; generating a profile path, and generating interpolation points according to a preset interval; constructing a spatial index structure based on the sounding data set, and establishing an adjacent sounding point retrieval channel for each interpolation point; and in allusion to the same profile path, acquiring multiple periods of sounding data, calculating water depth difference, and dynamically and visually displaying an abnormal movement phenomenon by using a broken line graph. According to the method, efficient extraction, dynamic comparison and automatic early warning of the multi-period sounding data can be realized, and the analysis efficiency and accuracy of the channel topographic change are remarkably improved.

The invention discloses a trademark retrieval library generation method and device based on a multi-modal representation generation model, and the method comprises the steps: constructing a trademark image-text pair according to a Vienna graphic element classification standard, and training the multi-modal representation generation model; constructing an initial trademark retrieval library by utilizing the trained multi-modal representation generation model; obtaining trademark rejection data, and performing fine adjustment on the trained multi-modal representation generation model by using an adapter technology and a triple contrast learning method to obtain an optimized multi-modal representation generation model; and regenerating a trademark image feature vector by using the optimized multi-modal representation generation model, and inputting the trademark image feature vector into a vector database to obtain a final trademark retrieval library. According to the trademark retrieval method, the trademark image-text pair and the trademark rejection data are utilized to finely adjust the multi-modal representation generation model twice, so that the overall retrieval effect of the trademark retrieval library constructed by utilizing the multi-modal representation generation model is improved, and the trademark retrieval result is more accurate.

A method includes: obtaining a first image including a target item; selecting a plurality of reference images corresponding to the first image from a database; performing word segmentation on item text information corresponding to the plurality of reference images to obtain a plurality of words; and extracting a key word meeting a reference condition from the plurality of words, and determining the extracted key word as an item name of the target item.

Example implementations include a method, apparatus and computer-readable medium of object / action recognition using a text-based classification model, comprising generating an image vector configured to represent one or more features of the first image. Additionally, the implementations further include computing a vector distance between the image vector and each of a first text vector and a second text vector, wherein the first text vector is configured to represent a first text, and wherein the second text vector is configured to represent a second text. Additionally, the implementations further include classifying the first image according to the first text or the second text based on which computed vector distance indicates a highest similarity between the image vector and either the first text vector or the second text vector relative to the other of the first text vector or the second text vector.

The invention discloses an automatic administrative boundary fusion charting method and a meteorological charting method based on a python language. Belongs to the technical field of meteorological charting, and particularly relates to the cross technical field of meteorological data processing and geographic information system visualization. The method starts with the construction of a multi-scale adaptive boundary fusion map, so as to solve the problems of cross-scale (such as province-to-village) precision faults and large interpolation errors of complex terrains, and achieve a cross-level administrative division boundary seamless aggregation technology (village level-town level-county level-province level). Therefore, the problem that precision is easy to lose when cross-scale conversion (such as from province to village) is carried out during meteorological mapping is solved.

A machine-learning algorithm is trained on images with a set of diverse items to produce as output feature vectors in a feature-vector space derived for the set. New item images for new items are passed to the algorithm and new feature vectors are projected into the vector space. A classifier for each new item is trained on the new feature vectors to determine whether the new item is new item or is not that new item. During a transaction, an item code scanned for an item and an item image are obtained. The item image is passed to the algorithm, a feature vector is obtained, a corresponding classifier for the item code is retrieved, the feature vector is passed to the classifier, and a determination is provided as to whether the item image and item code matches a specific item that should be associated with the item code.