43 results about "Visual structure" patented technology

The invention provides a front-end code evaluation method and system, electronic equipment and a program product, and the method comprises the steps: obtaining a front-end code, carrying out the compiling and rendering of the front-end code, and obtaining a generated front-end page and a target front-end page; performing code extraction processing on the generated front-end page and the target front-end page, and performing redundant node cleaning and code structure tree generation processing on extracted markup language codes to obtain a generated code tree and a target code tree; performing tree structure and element content error calculation processing on the generated code tree and the target code tree to obtain a content structure error; performing visual structure error calculation processing on the generated front-end page and the target front-end page to obtain a visual structure error; and according to the content structure error and the visual structure error, determining and obtaining an evaluation result for generating the front-end code. The scheme can improve the generation accuracy of the front-end code, and can be widely applied to the technical field of artificial intelligence.

A geometric structure aided visual localization method and a system implementing the method are provided. The method includes retrieving a 3D map of initialization location data, the 3D map being constrained by visual structures and geometric structures and modeled by a Gaussian mixture model of a set of Gaussian distributions with mapped landmarks; acquiring a series of real-time image frames by a camera of a mobile system; and for each real-time image frame: extracting local features from the real-time image frame; predicting a camera pose corresponding to the real-time image frame; creating a key frame by tracking the predicted camera pose in the 3D map; identifying temporally visible landmarks with respect to the created key frame; acquiring 2D-3D correspondences between the local features and the temporally visible landmarks; and localizing the mobile system by estimating a state of the real-time image frame based on the 2D-3D correspondences.

The utility model relates to a swimming suit technical field, specifically disclose a cover cup swimsuit with photo frame round hole structure, including cover cup cover and sponge cover cup, the surface of cover cup cover is equipped with hole body, cover cup cover covers on sponge cover cup, the front end face of sponge cover cup is outwardly convex through hole body, compared with the traditional collection of this technical scheme, and the process of saving position, the cover cup edition technology of wrinkle, this technical scheme replaces the collection of hole body cooperation cover cup protruding or wrinkle, from the effect, the surface has no trace of saving position or wrinkle, improves the aesthetic property, in addition, improves the three -dimensional penetrability of round hole, breaks through the planarization, the single limitation of traditional process, creates novel visual structure, product appearance has more discernibility and innovativeness, from the process, simplifies the complicated collection of saving position calculation, the operation such as wrinkle setting, reduces technical threshold and production difficulty, improves the edition efficiency and the finished product flatness, realizes multiple breakthroughs on structural rationality, appearance uniqueness, production convenience.

The invention relates to an adhesive dispensing area acquisition method and device and an adhesive dispensing method and device, which are used for installing a functional assembly on a base through retention glue, the retention glue at least comprises a first colloid, and the method comprises the following steps: acquiring edge information of a visual structure of the base; acquiring boundary information of the cavity of the base based on the edge information of the visual structure; obtaining size information of the functional component; obtaining a target placement position of the functional component in the cavity according to the boundary information of the cavity and the size information of the functional component; and based on the boundary information of the cavity and the target placement position of the functional component in the cavity, obtaining a dispensing area of the first colloid. According to the dispensing area obtaining method and device and the dispensing method and device, the dispensing precision and the mounting reliability of the functional assembly are improved, the packaging consistency is ensured, and the product yield and the production stability are further improved.

The invention discloses a suspicious person monitoring method and system for bank security and protection, and relates to the related field of image processing, and the method comprises the steps that a multispectral imaging device collects a person movement image data stream to construct a three-dimensional behavior image data body; constructing a virtual behavior simulation environment, generating a multi-path standard behavior track set, and constructing a behavior inertia reference map; executing cross-time-domain optical flow consistency analysis and local visual structure stability calculation of the data volume to construct behavior trajectory disturbance field distribution, and generating a behavior inertia damage degree distribution matrix based on a difference mapping relation with the atlas; carrying out micro-scale visual enhancement processing, and constructing a micro-action tensity tensor by utilizing sub-pixel-level jitter evolution detection and skin table reflection dynamic fluctuation analysis; and inputting the tensity tensor and the damage degree distribution matrix into a visual risk time sequence evolution channel to generate a suspicious risk evolution curve. The technical problem of limited identification precision in existing suspicious person monitoring is solved, and the technical effect of improving the identification precision is achieved.

The application provides a text branch-based AI conversation structure graph and a context dynamic assembly method. The method allows the user to open a new conversation unit as a text branch by designating the selected content as a context anchor from any conversation unit, thereby dynamically organizing the conversation into a visual structure graph with each unit as a node. The context dynamic assembly algorithm is based on the context anchor and the graph, intelligently evaluating the relevance of each historical conversation and the current input from the dimensions of semantic association, structural proximity, logical context, etc., and calculating the comprehensive weight and sorting for the most relevant content. Finally, the algorithm intelligently balances the fidelity and abstractness of the information at each level according to the sorting and the budget of the smallest semantic unit (Token), constructs a context load with optimal information density and dynamic fidelity, and provides it to the AI, significantly improving its understanding and response ability to the user's real intention in complex multi-threaded conversations.

The invention provides a digital twinning-oriented campus energy consumption intelligent management method, which comprises the following steps of: projecting data into a three-dimensional campus model by adopting a space mapping algorithm according to an obtained energy consumption data set, and determining a distribution position of a high-energy-consumption area; if the determined high-energy-consumption area exceeds a preset threshold value, real-time data fluctuation is analyzed through an anomaly positioning algorithm, and a potential anomaly source is judged; obtaining the judged abnormal source information, and decomposing the energy consumption level from a macroscopic panorama to a microscopic building by adopting a multi-level analysis method to obtain a layered visual structure; for the obtained structure, rendering a dynamic thermodynamic diagram through a visual expression technology to obtain a visual spatial distribution view; extracting functional characteristic data from the obtained view, generating an energy-saving measure suggestion for the building position by adopting a decision tree algorithm, and determining an optimization path; and through the determined optimization path, the feedback cycle of the energy consumption data set is updated, and a continuous monitoring intelligent management framework is obtained.

The application discloses a continuous children's picture book image generation method based on dynamic memory enhancement. The application firstly performs multi-stage cascading cleaning on original children's picture book images to construct a high-quality image-text pair dataset; inserts a consistency enhancement low-rank adapter into a pre-trained text conditional image generation base model to construct a dual-source dynamic feature memory bank; performs frequency domain decoupling processing on latent feature maps corresponding to reference images and historical images, extracts local edge, texture details and local structure information, and combines a time sequence attenuation bias to perform memory enhancement attention fusion; constructs an automatic preference sample based on a multi-modal visual evaluation model, trains a preference alignment low-rank adapter, and obtains a continuous picture book image generation model based on preference alignment. The application can improve the role appearance consistency, page coherence and visual structure rationality in the continuous picture book image generation process, and reduce the occurrence probability of role drift, style mutation and local structure anomaly in long sequence generation.

The application discloses a cross-domain cross-source data alignment method and system and electronic equipment. The method first inputs a plurality of sets of table data to be aligned. Then, key-value pairs in the data and positions of the key-value pairs in the table are extracted. Next, a data multi-modal representation model is used to generate vector expressions of the keys, values and visual positions. Semantic distances of the vector expressions from different data are calculated. Finally, the semantic distances between different data are evaluated to determine an alignment result. In addition to using pairing between keys, the application considers matching of values, enhancing matching of keys in the prior art. In addition to the representation in the text, the application fuses a table visual structure as part of semantic representation of the key-value pairs, breaking the limitation of the prior art that only uses single-modal information for matching.

The invention discloses a transient electromagnetic signal denoising method based on WTD-PC-ViT, and belongs to the field of geophysical electromagnetic data processing research, and the method comprises the steps: firstly carrying out the preliminary denoising of a noisy transient electromagnetic signal through employing an improved wavelet threshold denoising WTD method, and reducing the interference of a random noise signal on network training; then multi-scale feature extraction and time sequence modeling are carried out through a PC-ViT deep neural network, and self-adaptive suppression of residual random noise and enhancement of effective information are realized; according to the method, the time-frequency locality of wavelet analysis and the global feature capturing capability of a visual Transformer structure are fully combined, the signal-to-noise ratio of the denoised signal is remarkably improved, the output result is closer to an ideal real signal, and the method has high robustness and generalization capability so as to solve the problems that the signal-to-noise ratio of the late transient electromagnetic signal is low, and the signal-to-noise ratio of the late transient electromagnetic signal is low. And a traditional denoising method is difficult to effectively suppress random noise.

The invention discloses a document semantic restoration and stroke reconstruction method, system and device based on a condition control diffusion architecture and a medium, and belongs to the technical field of document image restoration, and the method comprises the following steps: extracting a visual structure condition, a semantic condition and a degradation condition of a degraded document image; respectively inputting the three types of conditions into corresponding encoders to obtain structure encoding features, semantic encoding features and degradation encoding features; inputting the three types of coding features into a diffusion model, respectively injecting the coding features at different network hierarchies through a layered injection mechanism, dynamically adjusting the weight according to the denoising progress, and generating a reconstructed image; performing coarse-grained restoration, fine-grained restoration and quality refining on the reconstructed image in sequence; semantic verification and visual evaluation are carried out on the repaired image, and a substandard region is positioned for key optimization; and outputting the optimized document image. According to the method, semantic understanding and stroke reconstruction are synchronously carried out through a multi-modal condition control mechanism and a layered injection strategy.

The utility model relates to a visual weighing and leakage detecting all-in-one machine which comprises a frame body, and a cover body is arranged on the front side of the top of the frame body. The visual structure is mounted on the right side of the frame body and used for visually detecting the appearance of the bottle; the weighing structure is mounted in the middle of the frame body and is used for performing standard detection on the weight of the bottle; and the side leakage structure is mounted on the left side of the frame body and is used for performing quality detection on sealing of the bottle. According to the utility model, visual detection, weight detection and side leakage detection are integrated, so that multiple detections of bottles can be automatically completed in a continuous production process, and the detection efficiency is remarkably improved; compared with a traditional single detection device, three detection functions are integrated, the number of devices needed on a production line is reduced, and therefore occupied space and production cost are reduced; according to the utility model, the functions of visual detection, weight detection and side leakage detection are integrated at the same time, so that the requirement of using a plurality of devices in series is reduced, and the production process and the production complexity are simplified.

This invention discloses a multimodal cognitive fusion collaborative processing system and method based on AI large-scale model technology. The system includes a large-scale model semantic understanding module, a visual language model parsing module, and a real-time collaborative decision-making unit. The decision-making unit dynamically fuses textual semantic features and visual structural features through a gating mechanism, driving iterative reasoning between the two modules to output structured cognitive results. This invention reduces the illusion rate of key fields under complex layouts, effectively reducing localization errors, and enables zero-sample generalization without templates. Consistent iteration significantly shortens manual review time and greatly improves batch processing efficiency. It incorporates financial-grade security mechanisms such as encryption, auditing, and disaster recovery, providing a general foundation for highly reliable document understanding. The system adopts a microservice architecture, supports elastic deployment on cloud, edge, and client, has fault self-healing and fine-grained permission control capabilities, can be seamlessly integrated into existing business processes, maintains long-term self-evolution, is suitable for various high-compliance scenarios, and significantly reduces operational and legal risks.

This invention provides a method and system for early-stage rumor detection on social media based on the PGQH-TE model, belonging to the technical field of social media content security and information authenticity identification. It includes: encoding each early rumor event into a text modality and a grayscale image modality; extracting a global semantic prior vector from the text using a BERT model, and using this to guide an improved BiGRU network to extract text sequence features, an improved ResNet-18 network to extract visual structural features, and a specially designed parallel variational coding and bit-level adaptive fusion quantum hybrid network PVBF-QHN to extract quantum state features from the prior vector; projecting the text, visual, and quantum modal features into spatial point charges using a triangular electrostatic field Coulomb fusion method, and achieving lossless fusion of high-order cross-modal interactions based on electrostatic potential and potential gradient, thus realizing early-stage rumor detection on social media. This invention can achieve high-accuracy automatic identification of social media rumors in early-stage scenarios with highly sparse information.

The invention discloses a chemical scene monitoring method and system based on multi-task visual structured information, and the method specifically comprises the steps: firstly, collecting a chemical monitoring scene image and depth information in real time through a depth binocular camera, constructing a scene depth map, obtaining the information of various objects in the scene through a target detection module, and carrying out the detection of a worker target, a key point detection module is used for extracting coordinates and attitude features of key parts, and multi-key-point attitude feature representation of the object is formed; then collecting original point cloud data by using a laser radar, and carrying out correlation calculation on the point cloud data and an object position to obtain an accurate three-dimensional space coordinate; performing data fusion to generate structured description data of the chemical monitoring scene; and finally, based on the structured description data, analyzing and judging behaviors and potential risks of workers through a risk reasoning algorithm, and generating a risk judgment result. According to the invention, the environment perception and risk identification capabilities of the robot are enhanced, and the safety monitoring level of the robot in a chemical scene is improved.

A kind of multi-feature three-dimensional reconstruction 3D Gaussian method based on laser vision, comprising: aligning laser radar point cloud and camera image by space-time calibration, establishing unified coordinate system;Geometric features are extracted using point cloud data obtained by Lidar point cloud, and Gaussian ellipsoid is initialized according to Lidar point cloud;The brightness, contrast and structural similarity of rendered image and real image are optimized in combination with mean absolute error L1 and structural similarity SSIM;The curvature of forced K nearest neighbor Gaussian ellipsoid is consistent, and the major and minor axes of aligned Gaussian ellipsoid are combined with line and surface features to reduce geometric distortion;The distribution density of 3D Gaussian is dynamically adjusted through line / surface features and visual structure information extracted by Lidar, to realize the balance between geometric detail enhancement and calculation efficiency.The position, scale and rotation parameters of Gaussian are uniformly optimized, the consistency of model structure is improved, and the details and calculation efficiency of model are balanced.

This utility model relates to an easy-to-install circuit breaker, comprising a circuit breaker body and a mounting base, wherein the circuit breaker body is detachably mounted on the mounting base. The outer surface of the circuit breaker body is provided with color-coded markings to indicate the functional types of the wiring terminals; the mounting base is provided with directional arrows to indicate the correct installation direction; the circuit breaker body is provided with an alignment window to allow viewing of the alignment marks on the base for precise positioning. By setting up the above-mentioned visual structure, installation identification is effectively improved, the risk of misinstallation is reduced, and construction efficiency is increased.

The utility model relates to the technical field of cold storage door demisting, and discloses a cold storage door demisting device with a visual structure, which comprises a mounting frame, a cold storage door body is mounted at one end of the mounting frame, an observation window is mounted in the cold storage door body, an air outlet is formed in the bottom end of one end of a demisting box, and an air outlet is formed in the bottom end of the other end of the demisting box. A support is mounted on one side of the top end of the cold storage door body, a mounting base is mounted at one end of the bottom end of the support, an anti-freezing camera is mounted at the bottom end of the mounting base, and a display panel is mounted at the other end of the cold storage door body. The display panel, the anti-freezing camera, the mounting seat, the bracket and other components are arranged on one side of the cold storage door body, so that the demisting equipment has a visual structure, and the demisting equipment can shoot the working process of demisting mist on the inner surface of the observation window in the cold storage door body; therefore, a worker can conveniently know the demisting working condition of the observation window, and the use is more convenient.

The application discloses a kind of bird image recognition analysis methods based on computer vision, comprising the following steps: obtaining input image containing bird target, generating structure node set and structure relationship diagram;Analysis structure node combination relationship, generate structure lock candidate set;To candidate structure mode distribution structure lock credibility, generate structure lock credibility sequence;Structure energy propagation relationship is built, and structure energy propagation result is generated;Update structure node relationship state, generate visual structure evolution sequence;Calculate structure node energy distribution and judge whether into preset structure stable domain;Identify the node combination that leads to structure instability and update structure lock candidate set;When candidate structure mode enters structure stable domain, the corresponding bird recognition analysis result is output.The application realizes bird image recognition by structure energy propagation and visual structure evolution analysis, with the advantages of high recognition stability and strong analysis ability.

This invention discloses a method and system for detecting social media rumors based on the BLRQ-BV model, belonging to the technical field of social media content security and information authenticity identification. It includes: encoding each rumor event as a whole into a text modality and a grayscale image modality, constructing a bimodal data representation that maintains semantic integrity; using a BiLSTM network to extract sequence features from the text, employing a specially designed low-discrimination-information-loss quantum hybrid network LIL-QHN to extract quantum features from the text, and using a ResNet-18 network to extract visual structural features from the grayscale image; losslessly fusing the three modal features through an innovative spherical spatial vector synthesis method VC-BS, preserving the feature strength and directional relationships; and introducing a joint loss function to collaboratively optimize each branch, ultimately achieving end-to-end rumor detection. This invention can robustly achieve automatic identification of social media rumors and is applicable to scenarios such as network content security management, public opinion monitoring and early warning, and digital forensics.

The application discloses an automatic Web UI test method and system based on a visual language model, which comprises the following steps: parsing a test task set containing operation actions and target objects from a test script; based on a Web interface screenshot and an accessibility tree, respectively extracting a visual interface element set and a structured interface element set through a visual language model and rule analysis; using a multi-modal semantic alignment algorithm to fuse the visual and semantic features of the two types of elements to generate a complete interface element set; inputting the test task and the complete element set as context prompts into the visual language model to drive it to generate interface observation, semantic reasoning and operation through iteration to execute the test. The application fuses multi-source information of vision, structure and semantics to realize end-to-end automatic mapping of natural language test tasks to accurate UI operations, and significantly improves the accuracy, robustness and generalization ability of the test in dynamic interfaces and cross-platform scenarios.

Disclosed in the present invention is a single-frame real-time three-dimensional imaging method based on deep learning, comprising: constructing a lightweight phase retrieval network model based on a physical model; building a multi-vision structured light fringe projection system; constructing a training data set to complete training of the lightweight phase retrieval network model; and using TensorRT to deploy the lightweight phase retrieval network model. Three wrapped phase images are obtained in real time by means of parallel reasoning of three monochromatic view angles; wrapped phases are unwrapped into absolute phases by using a multi-view geometric constraint and three-dimensional phase matching algorithm; and a three-dimensional point cloud having color texture information is generated by means of phase-height mapping and a color image. In the present invention, deep learning technology is integrated with a conventional fringe projection physical model, such that rapid phase acquisition can be achieved using only a single image frame, thereby overcoming motion interference and enabling online, real-time, high-precision three-dimensional imaging in complex dynamic scenes.

A question-answering system that receive a natural-language question includes a database to provide a basis for that answer and a structured-query generator that constructs a structured query from the question and uses it to obtain an answer to the question from the database.

This application proposes a front-end code evaluation method, system, electronic device, and program product. The solution involves acquiring front-end code, compiling and rendering it to obtain a generated front-end page and a target front-end page; extracting code from both the generated and target front-end pages, and cleaning up redundant nodes and generating a code structure tree from the extracted markup language code to obtain a generated code tree and a target code tree; calculating the tree structure and element content errors in both the generated and target code trees to obtain the content structure error; calculating the visual structure error in both the generated and target front-end pages to obtain the visual structure error; and determining the evaluation result of the generated front-end code based on the content structure error and visual structure error. This solution can improve the accuracy of front-end code generation and can be widely applied in the field of artificial intelligence technology.

The utility model provides a foot cup polishing device with a protection function, which relates to the technical field of servo motor foot cup production, and comprises an operation table top, a three-axis clamp structure is arranged at the top of the operation table top, a polishing machine is arranged on the back side of the three-axis clamp structure, a driving structure is arranged on the back side of the operation table top, and the polishing machine is arranged on the back side of the operation table top. A protective frame structure is arranged at the connecting position of the driving structure, a detachable visual structure is arranged in the protective frame structure, the detachable visual structure and the protective frame structure can be rapidly disassembled and assembled, and the protective frame structure can ascend or descend through the driving structure. Splashing chippings in the polishing process are effectively blocked, workers are prevented from directly getting close to the running polishing machine, potential safety hazards are greatly reduced, a safer operation environment is provided for the workers, and the side plates of the protection frame structure are connected with the mounting frame through the connecting pieces, the fixing screws and the locking nuts.

The invention discloses a steel identification intelligent identification method and system based on deep learning. The method comprises the following steps: carrying out image acquisition and preprocessing to form a preprocessed steel surface image sequence; constructing a hierarchical time sequence memory network and completing structure initialization; positioning a steel identification area, and generating a steel identification area image sequence; extracting steel identification visual structure features and encoding to generate a sparse distributed representation sequence; performing time stability judgment and outputting a stable time interval index set; generating a character sequence prediction state sequence according to the stable time interval index set; executing time consistency judgment to determine a steel identification recognition result; performing combination legality verification, and generating coding rule consistency constraint information; information is fed back to the memory updating process, and a steel identification recognition result subjected to coding rule consistency constraint is output. Layered time sequence memory deep learning is utilized, steel material identification time sequence consistent identification is achieved, and the method is high in stability and reliability.

The utility model provides a visual structure of an electric cooker, which relates to the field of electric cookers and comprises a base, an outer cover is fixedly mounted at the top of the base, an inner container is embedded in the inner wall of the outer cover, a heating component is mounted on the inner wall of the inner container, a placing support is mounted at the top of the heating component, and a rice hopper is mounted at the top of the placing support. The outer cover, the inner container and the rice hopper are all made of transparent high borosilicate glass materials and are good in heat stability, high in heat conductivity, good in chemical stability and high in transparency, so that the internal situation can be seen when the device works, the two sliding blocks are opened by pulling the two sliding handles, the stabilizing blocks are opened along with the two sliding blocks, and therefore the device is convenient to use. When a connecting line is connected, the connecting line body is inserted into the device, then the sliding handle is loosened, the two sliding blocks move towards the middle through the elasticity of the spring, the stabilizing block clamps the connecting line body, and the connecting line is fixed after being connected.

The application discloses a kind of based on deep learning's electric power measurement field target detection method and system, belong to electric power measurement field target detection technical field.The method of the present application, comprising: obtaining the field image information of electric power operation field, generates the image data of the electric power operation field;Based on the representation evolution mechanism of measurement object, according to the image data, generate the visual structure response result for representing the existence state and the form distribution of the measurement target of the electric power operation field;Based on the constraint mapping mechanism of measurement scene, the saliency intensity of candidate measurement target in the visual structure response result is judged;Based on the determination result, the human interaction behavior of electric power operation field is identified.The implementation of the present application not only makes it necessary to proceed in order according to steps in the process of electric power operation, but also can improve the stability and accuracy of target detection under complex electric power measurement field conditions, with good engineering applicability.

The application discloses a task execution method, an electronic device and a computer program product, and belongs to the technical field of communication. The method comprises the following steps: in response to receiving a target task, determining an initial task evolution framework corresponding to the target task; the initial task evolution framework is generated based on a preset visual structure, wherein the initial task evolution framework comprises a plurality of nodes, and the plurality of nodes correspond to each link of task evolution in the process of the target task from task input to task execution end; based on task execution data of each link of task evolution, updating metadata of the corresponding node in the initial task evolution framework to obtain a complete task evolution framework of task execution of each link after the target task is executed, wherein the metadata of each node in the initial task evolution framework is used to carry task execution data of the corresponding link of task evolution.

This disclosure relates to the field of object evaluation technology, and provides a method, apparatus, electronic device, and readable storage medium for evaluating the state of a business object. The method includes: performing visual structuring processing on a visual image to be processed to obtain a target region mask image; performing feature extraction processing on environmental audio data and business data to be processed to obtain audio feature vectors and structured keyword data; performing multimodal recognition processing on the target region mask image, audio feature vectors, and structured keyword data respectively to obtain visual feature vectors, audio feature vectors, and text feature vectors; performing cross-modal attention fusion processing on the above feature vectors to obtain fused feature vectors; and performing gradient boosting processing on the fused feature vectors to obtain the target business object state evaluation result. This improves accuracy, enhances understanding, increases processing efficiency and robustness of the evaluation results, improves adaptability, and enhances dynamic iteration capabilities.