98 results about "Object matching" patented technology

The invention relates to a visual inspection method and system based on an industrial personal computer, and the method comprises the steps: collecting an original image of an industrial product through an industrial camera, and carrying out the preprocessing of the original image, and obtaining a standardized image; based on a standardized image, global features and multi-scale local features of the image are extracted through a CLIP visual encoder, multi-granularity text prompts are generated, the multi-granularity text prompts comprise image-level global prompts and block-level local prompts, and deep interaction of the text and the visual features is realized through a multi-scale convolution kernel and a multi-head cross attention mechanism. Obtaining a pixel-level structure defect anomaly score graph; based on the standardized image and a preset normal sample reference library, generating a logic anomaly score graph through cross-modal semantic alignment and object matching; and carrying out fusion scoring on the structural defect anomaly score graph and the logic anomaly score graph by adopting weighted fusion, carrying out anomaly judgment based on fusion scores, and carrying out display on an industrial personal computer interface based on the anomaly judgment.

An apparatus for detecting an object using a radar sensor and an image sensor includes an object sensing unit configured to: sense a first object through the radar sensor installed to sense a target road and sense a second object through the image sensor installed to sense the target road; an object matching unit configured to match the first object with the second object; a lookup table management unit configured to generate a lookup table for the target road based on the first object and the second object which are matched with each other; and a complementation unit configured to complement a sensing result from the radar sensor or a sensing result from the image sensor based on the generated lookup table.

An artificial intelligence-based integrated port management system, relating to the technical field of integrated port management. A ship data acquisition terminal is used for: acquiring ships appearing within a set location during a set time period, marking the ships as pending objects, synchronously acquiring standard information representing the dimensions of the pending objects, and transmitting to a main control terminal a pending object set consisting of multiple pending objects and the standard information thereof; and at the same time, synchronizing remaining berths among ship berths of a port and their corresponding berth adaptation values, wherein the matching between a berth adaptation value and standard information determines whether a pending object can be berthed in a corresponding remaining berth. Then, the main control terminal is used for performing one-to-one combination matching on all the pending objects and the remaining berths to obtain multiple object matching combinations, and then determining selected object combinations on the basis of a remaining value of each object matching combination. A first round of berth matching can be first performed on the basis of time periods and scenarios, and when there are no berths available subsequently, flexible scheduling can be achieved.

The application discloses a target coordinate positioning system and method based on a multi-view panoramic camera, relates to the technical field of target coordinate positioning, and comprises the following steps: evaluating the spatial geometric relationship between different camera units; performing target object detection on images to obtain to-be-determined target objects in the images, and screening the to-be-determined target objects in the images in combination with historical images; evaluating the comprehensive cost between the target objects in the images and candidate matching objects in other images, constructing a target cost matrix between the images and the other images and solving the target cost matrix; performing image feature fusion on the images according to the target object matching data between the images, obtaining a fused image, obtaining the three-dimensional coordinates of the target objects in the fused image and collecting the three-dimensional coordinates to obtain target coordinate data in the fused image, so that more target objects can be detected, and accurate positioning of the target objects can be realized.

This invention discloses an automatic browser memory leak location system, method, and medium based on the MCP protocol, belonging to the field of software testing technology. The system includes an MCP communication module, an automated testing module, a heap snapshot acquisition module, an incremental analysis module, a reference chain analysis module, a SourceMap location module, an intelligent repair module, and an IDE visualization module. This invention establishes a standardized connection between the IDE and the browser debugging port through the MCP protocol, achieving fully automated control; it employs a multi-dimensional fingerprint algorithm based on constructed stack frames and attribute structures to solve the problem of cross-snapshot object matching; it utilizes the dominator tree algorithm to compress the reference chain and combines it with the SourceMap index to achieve source code-level location and AI repair suggestion generation. This invention significantly improves the efficiency and accuracy of memory leak location, solving the problems of fragmented debugging links and the inability to accurately map source code.

Provided are a search assistance system, a mobile body device, a search assistance method, and a recording medium which are capable of contributing to improvement of efficiency of search for a search target.　The search assistance system comprises: an acquisition means which acquires, as information on a search target, a feature amount extracted from an image of the search target; a distribution means which includes an object matching function using a camera and the feature amount and distributes the feature amount extracted from the image of the search target to a mobile body cooperating in the search for the search target; a reception means which receives, from the mobile body, a report including information for identifying the position of the mobile body and including whether or not an object corresponding to the feature amount extracted from the image of the search target has been found; and a recording means for recording, on the basis of the report, a section which is searched for the search target by the mobile body.

The application relates to the technical field of object matching, in particular to a context-based object matching method and device, terminal equipment and a storage medium, wherein the method comprises the following steps: based on context information of a target object in an information source, at least one attribute of the target object is extracted, and an attribute set of the target object is constructed according to the at least one attribute of the target object; then, attribute sets of at least one candidate object in a preset database are acquired, similarity matching is performed on the attribute set of the target object and the attribute sets of the candidate objects, and the similarity of the target object and the at least one candidate object is obtained; and finally, a matching result between the target object and the at least one candidate object is determined. Therefore, the problems of matching limitations, high error rate and incomplete information completion in processing object recognition and alignment in multi-source heterogeneous data due to the fact that the prior art relies on fixed attributes, context utilization is insufficient and correlation reasoning capability is insufficient in the related art are solved.

The application relates to an object matching method and device, computer equipment, a computer readable storage medium and a computer program product, which can be applied to various scenes such as cloud technology, artificial intelligence, intelligent transportation and auxiliary driving. The method comprises the following steps: acquiring an object screening condition comprising a plurality of sub-screening conditions, determining each screening level nested in the object screening condition, and determining the level condition of each screening level according to the nesting relationship between the screening levels; for each screening level with a subsequent screening level, adding a candidate object in a candidate object set of the screening level to a candidate object set of the subsequent screening level; the matching result of the candidate object and the level condition of the screening level meets the matching condition of the screening level; and screening a target object matching the object screening condition from the candidate object set of the last screening level. The above method can improve the work efficiency of the object matching process.

The embodiment of the invention provides a target recognition method and system, processing equipment and a storage medium, and relates to the technical field of computer vision. The method comprises: acquiring a to-be-recognized image; inputting the to-be-recognized image into a pre-trained target feature extraction model, and obtaining a target feature of a target object output by the target feature extraction model; based on a current object feature library and the target features, determining an object matching result of the target object, the current object feature library including registration features of registered objects; and based on the target features and the object matching result, updating the current object feature library, and returning to the step of obtaining the image to be recognized so as to perform target recognition by using a new current object feature library. In this way, the current object feature library is updated by using the object features obtained in the target recognition process and the object matching result, and the accuracy of the target recognition result can be improved.

The invention relates to a natural language query method and system, computer equipment and a readable storage medium. The method comprises the steps that under the condition that a query input request of a natural language type is received, the query input request and an intermediate query language rule are assembled into a cue word, the cue word is input into a large language model, and the cue word is used for guiding the large language model to recognize a to-be-queried field object in the query input request, determining at least one piece of candidate query field meta-information matched with the to-be-queried field object, and generating an intermediate query statement conforming to an intermediate query language rule according to the query input request and the at least one piece of candidate query field meta-information; obtaining an intermediate query language statement generated by the large language model, analyzing the intermediate query language statement into an abstract syntax tree, and converting the abstract syntax tree into a standard query statement; and performing data query through the standard query statement to obtain a query result. The method can improve the accuracy of natural language query.

The embodiment of the disclosure provides a method, apparatus, device, and storage medium for object recognition. The method includes: determining a set of first candidate object regions based on image information of a media content; determining, based on text information associated with the media content, an object region from the set of first candidate object regions; and determining an object matching the object region based on a visual feature of the object region and a text feature, the text feature being determined based on the text information. Based on the manner, disclosure may recognize an object in the media content for multimodal information of the image information of the media content and text information associated with the media content, which may effectively improve the accuracy of the object recognition.

Embodiments of the present application provide an image generation method, a reward model training method, an electronic device, a storage medium and a computer program product. The method comprises: obtaining object description text of a target object, original object image and scene information matched with a to-be-generated image carried by an image generation instruction; taking the scene information, the object description text and the original object image as input information, calling a pre-tuned visual language model to generate background image design description text adapted to the scene information, wherein when the scene information is a weak signal in the input information, the background image design description text can reflect scene preference characteristics matched with the scene information; calling a preset image generation model to generate an image of the target object matching the scene information under the constraint of the background image design description text, the image of the target object in the original object image and layout information. The image generated by the method is more matched with the scene preference corresponding to the scene information.

This application discloses a data processing method, apparatus, device, and readable storage medium based on blockchain. The method includes: obtaining a first object matching request sent by a first node for a first object; invoking an evaluation smart contract in the blockchain based on the first object matching request, and obtaining a first evaluation parameter of the first object in the blockchain through the evaluation smart contract; invoking a matching smart contract in the blockchain based on the first evaluation parameter, and obtaining second evaluation parameters corresponding to N second objects contained in the matching pool through the matching smart contract; determining the parameter differences between the N second evaluation parameters and the first evaluation parameter, and determining the competing objects of the first object among the N second objects contained in the matching pool based on the N parameter differences. Using this application, in game matching services, the transparency of game matching can be supported, the accuracy of game matching can be improved, and thus game activity can be increased.

The application discloses a virtual object matching method and device in a complex environment, comprising: determining a sparse three-dimensional point cloud of a target based on a camera pose, and obtaining depth image (RGB-D) information of the target; combining the RGB-D information with the sparse three-dimensional point cloud to obtain a dense three-dimensional point cloud; removing outliers in the dense three-dimensional point cloud by using a specified bilateral filter, and weighting adjacent points by using an improved Gaussian weighting function; sampling based on the dense three-dimensional point cloud and a normal vector of each point calculated to obtain key points; calculating feature descriptors of a virtual model and a real scene based on the key points obtained by point cloud sampling to estimate the corresponding relationship between the two point clouds; and completing transformation estimation according to the corresponding relationship to realize matching of the virtual object and the real scene. The method can improve the stability, accuracy and real-time performance of matching of the virtual object and the real object in markerless augmented reality.

A computer-implemented method, the method comprising: accessing an image of a sample; detecting one or more shapes in the image; constructing a virtual map based on the detected one or more shapes in the image and a set of virtual map construction rules; and automatically navigating to a target area of the sample based on the virtual map to process the sample using a charged particle beam microscope. Another method includes accessing dynamically obtained shape data associated with an image of a sample; detecting one or more shapes in the image and converting the detected one or more shapes into found shape data; accessing artificial reference shape data; comparing the found shape data with the artificial reference shape data by object matching optimization to determine an alignment between the found shape data and the artificial reference shape data; and navigating to a target area of the sample based on the alignment.

The application relates to the computer technical field, and in particular to an information prompting method and device, electronic equipment and a storage medium, to improve the pertinence and reach rate of information prompting. The method comprises the following steps: obtaining content feature information of each multimedia content; obtaining statistical feature information of each multimedia content based on historical behaviors of each object to each multimedia content; obtaining information prompting time points of each multimedia content based on the obtained content feature information and statistical feature information; screening out target objects matched with each multimedia content based on content embedding vectors of the multimedia content and object embedding vectors of the associated objects; and prompting target information to the corresponding target objects when each multimedia content plays to the corresponding information prompting time point. The application realizes personalized intelligent information prompting by object matching and information prompting time point prediction, and effectively improves the pertinence and reach rate of information prompting.

The invention discloses an airport resource allocation optimization method and system based on scene triggering, and the method comprises the steps: S1, recognizing and triggering at least one current operation scene based on obtained real-time operation data, and carrying out the recognition and triggering of at least one current operation scene based on a mapping relation between a predefined operation scene and a constraint rule for airport resource allocation; determining a constraint rule set which is associated with the current operation scene and is started; s2, based on a pre-configured object matching condition, screening out a constraint rule matched with the current to-be-allocated airport resource and flight from the constraint rule set; s3, dynamically adjusting scores of the screened constraint rules based on the current operation scene to obtain a scene total score of each constraint rule in the current operation scene; and S4, based on the scene total score, performing allocation optimization on the airport resources and flights to be allocated, and outputting an optimized allocation scheme. According to the method, the dynamic adjustment of the resource allocation strategy along with the change of the operating environment is realized.

This application discloses an image matching method, apparatus, device, storage medium, and computer program product, relating to the fields of artificial intelligence and data processing technology. The method includes: identifying a first image and a second image respectively to obtain n objects in the first image and m objects in the second image, where n and m are positive integers; matching the descriptive term sets corresponding to the n objects and the descriptive term sets corresponding to the m objects respectively to obtain a first matching result between the first image and the second image; wherein, the descriptive term set corresponding to each object contains descriptive terms used to describe the features of the object, and the first matching result is used to characterize whether there are identical objects in the first image and the second image. This application, by supporting image-level object matching, reduces the mismatch rate of objects compared to one-to-one object matching because it comprehensively considers the matching degree between various objects, thereby improving the object matching accuracy.

The invention discloses a video object cross-frame association method and system, and relates to the technical field of computer vision and video analysis. Comprising the following steps: acquiring a plurality of sampling frames containing pedestrian objects in a to-be-processed video; for each sampling frame, performing target detection on the sampling frame to obtain a bounding box of a pedestrian object in the sampling frame; performing pixel-level semantic segmentation on the bounding box of the pedestrian object to obtain a pixel-level mask of the pedestrian object; performing motion detection on the pixel-level mask of the pedestrian object to obtain a moving target object; and performing association matching on the moving target objects in all the frames in the to-be-processed video and the historical target through a multi-modal matching decision to obtain a moving target object matching result. According to the method, the detection results of the same pedestrian object can be associated to the same target trajectory, and the identity retention capability and the trajectory matching precision in the video object cross-frame association process are remarkably improved.

To provide an object verification system which can perform object verification so as to maintain precision while improving calculation speed.SOLUTION: An input unit accepts input of a plurality of maximum matching solutions between a first node in which each target object detected in a first frame is considered as a node of one group of a bipartite graph, and a second node in which each target object detected on the basis of the frame up to a second frame adjacent to the first frame is considered as a node of the other group of the bipartite graph. An integration unit integrates a second maximum matching solution into a first maximum matching solution selected from among the plurality of maximum matching solutions to generate a portion graph, and when the node with an order of 2 exists in at least one type of node among the first node and the second node in the generated portion graph, generates the graph in which an edge is replaced so that the order becomes 1, according to the weight of the edge of the portion graph, as an integrated solution.SELECTED DRAWING: Figure 18

The invention relates to the field of information processing, and discloses an object monitoring method and device based on the industrial Internet of Things and a storage medium, an accurate real-time monitoring video is acquired through a multi-view image acquisition module, identity authentication is completed in combination with object features, object types are associated, and the problem that identity authentication and compliance control are disjointed is solved; meanwhile, real-time video estimation compliance is analyzed in a customized mode based on object types, and the defects that behavior analysis is poor in pertinence and inaccurate in quantification are overcome; moreover, risk video frames are extracted, historical frame traceability is combined, cross-frame object matching is matched, a risk link is restored, and the problems of lagging of single-frame detection and misjudgment and missed judgment are solved. In addition, background construction suitability is indirectly optimized through differential compliance verification logic, and monitoring accuracy and real-time performance are effectively improved.

The application provides a matching method and device, a storage medium and an electronic device. The method comprises the following steps: determining a to-be-recognized detection frame corresponding to a to-be-recognized image and a target detection frame, wherein the to-be-recognized detection frame contains a detected to-be-recognized object, and the target detection frame is determined based on a target object; in the case that it is determined that the to-be-recognized detection frame and the target detection frame are not matched, determining a to-be-matched feature of the to-be-recognized object in the to-be-recognized image; and determining a matching degree of the to-be-recognized object and the target object based on the to-be-matched feature. By using the technical solution, the problem that the success rate of object matching is low due to the fact that the target is easily blocked in the related art is solved.

A system for utilizing machine learning models and other technologies to process, organize, and manage tangible object and associated metadata is provided. The system captures media content of an object in an environment and analyzes the media content to identify the object. The system determines whether the object matches an object in a profile of a user. If the object matches the object in the profile, the system retrieves metadata associated with the object from the profile to provide further context for the object. The system updates the metadata for the object and stores the updated metadata in the profile. If the system determines that the object does not match an object in the profile, the system determines that the object is a new object and adds the object to the profile. The system generates and stores metadata associated with the new object in the profile to track the object.

The invention relates to the technical field of computers, in particular to a lightweight cloud file universal processing device and method and a storage medium, and the method comprises the steps: generating a plug-in matching request after receiving a cloud space object extension operation request; generating an executable plug-in list according to a plug-in interaction protocol in combination with an object matching rule; plug-in selection, input parameters and output parameters are received, and a plug-in execution request is generated; and distributing a plug-in execution instance for the plug-in execution request, creating the plug-in execution instance when no idle instance exists in an instance pool, loading a target plug-in code to execute cloud file processing, generating a processing result, and providing a task state and a cloud space object identifier of the processing result to an interaction side. According to the invention, through plug-in access and elastic scheduling, rapid expansion of processing capability, unified execution of interfaces and efficient utilization of resources are realized.

The invention discloses a position and influence-oriented precipitation echo near-real-time simulation and correction method, which comprises the following steps of: performing primary correction on near-real-time radar precipitation echo data by using near-real-time lightning data through a lightning-radar reflectivity inversion model, and performing secondary correction on the near-real-time radar precipitation echo data by using near-real-time automatic station precipitation data; performing secondary correction on the radar rainfall echo reflectivity data after the primary correction through an established rainfall rate model to obtain corrected real-time radar echo rainfall data; recognizing a storm object in the radar echo through a multi-threshold object recognition algorithm; performing radar echo object matching based on a Hungary solution, performing identification tracking on the identified storm object, and calculating the echo rainfall intensity, the influence range, the moving speed and the moving direction of the storm object; and the influence of the storm object is judged according to the position of the user, and real-time storm alarm service is carried out. According to the invention, position and influence-oriented rainfall professional meteorological services are provided for users through near real-time lightning, automatic station rainfall, radar and other multi-source data fusion technologies.

The application provides a kind of intelligent automatic door sound control method and system, it is related to intelligent control technical field.The method includes the voiceprint control data of authorized object is collected, and voiceprint control database is established;Real-time voice control detection data is obtained and is combined with voiceprint control database to carry out object identification based on voiceprint feature, and real-time target object is determined;Object sound control feature information extracted in voiceprint control database is combined with real-time voice control detection data to carry out matching analysis based on object feature, and object matching analysis result data is formed;According to object matching analysis result data, control analysis is carried out, and object sound control data is formed.The method is extracted by using intelligent technology to the sound data of the automatic door needing control, and effective and accurate comparison identification is carried out, and then the high recognition control effect of automatic door based on sound data is realized, and the application range and scene of automatic door are effectively expanded.

This application relates to an object recommendation method, apparatus, computer device, computer-readable storage medium, and computer program product. The method includes: displaying a selection area in response to an interactive operation instructing the recommendation of an object; displaying a batch of attribute options for the object in the selection area; updating the displayed attribute options in the selection area to another batch of attribute options for the object in response to selecting at least one attribute option from the attribute options displayed in the selection area; and displaying a recommended object in response to the end of the selection of attribute options for the object, the recommended object matching the selected attribute options. This method enables accurate object recommendation.

Implementations relate to methods, systems, and computer-readable media for performing similarity analysis of three-dimensional (3D) objects. In some implementations, the method includes obtaining a 3D model of the object that includes a mesh and a texture, encoding the mesh into a mesh feature vector using a first neural network, encoding the texture into a texture feature vector using a second neural network, computing a mesh distance between the mesh feature vector and a reference mesh feature vector of a reference object, computing a texture distance between the texture feature vector and a reference texture feature vector of the reference object, determining, based on the mesh distance and the texture distance, whether the object matches the reference object, classifying the object as a dissimilar object if the object does not match the reference object, and classifying the object as a similar object if the object matches the reference object.

The invention discloses a regional cathode protection potential balance algorithm. The algorithm specifically comprises the following steps: S1, real-time data acquisition; s2, real-time data preprocessing; s3, performing real-time state evaluation and adjustment object matching; s4, establishing and updating a real-time response model; s5, real-time adjusting quantity calculation and safety control are carried out; and S6, performing adjustment and iteration termination in real time. The method has the advantages that the real-time response speed is increased, the traditional hour-level adjusting period is shortened to the second-level adjusting period, adjustment is started after potential unbalance is carried out for 30 seconds or less, and the risk of short-term corrosion of a pipeline is avoided; due to the real-time model and coupling correction, the potential range is smaller than or equal to 0.08 V, the standard deviation is smaller than or equal to 0.03 V, and the method is superior to a traditional algorithm; the characteristics of a real-time acquisition control type intelligent potentiostat and a real-time data acquisition intelligent test pile are completely matched, and the real-time advantage of the equipment is exerted; and multi-dimensional real-time verification (step length, coupling, current and potential rate) is realized, and the risk of overshoot or equipment overload is avoided.