22results about How to "Efficient and accurate identification" patented technology

This invention provides a method, device, electronic device, and storage medium for detecting illegal dog walking incidents. The method fully utilizes the characteristics of the leash, designs a leash detection model to detect inclined target leashes, and designs a human-dog-leash relationship judgment model to detect the interaction between the human and the leash and / or the interaction between the leash and the dog. Thus, the detection results of illegal dog walking incidents determined based on the interaction between the human and the leash and / or the interaction between the leash and the dog are more accurate. In addition, the entire process is completed automatically and has good intelligence.

The invention provides a data processing method. The data processing method comprises the following steps: dynamically adapting a protocol of an external system; collecting source data from an external system; performing primary processing on the source data, removing redundant data, and retaining target data; providing an empty data table, performing secondary processing on the target data, writing the target data into the empty data table, and generating a real data table; processing the data in the real data table for three times to generate a declarated data table, and declaring the declarated data table to an external system; receiving an audit receipt from an external system; performing finance and taxation compliance auditing on the declarable data table according to a receipt result; and notifying an external system to complete subsequent operation. According to the data processing method provided by the invention, the protocol of the external system is dynamically adapted, the external system is flexibly connected, and the cooperation efficiency is improved; in addition, uneven resource allocation of the execution units is avoided through an intelligent scheduling algorithm, and efficiency and stability are improved under high concurrency. The invention further provides a data processing system used for executing the data processing method.

The application discloses a kind of intelligent basketball live broadcast systems based on man-machine cooperation, belong to automatic live broadcast technical field.It includes: mobile terminal device, two-dimensional holder and PC end management system;Mobile terminal device is used to real-time acquisition ball game picture, and obtains live broadcast focus coordinates by target detection to ball game picture;Two-dimensional holder is used to change control signal pulse width based on live broadcast focus coordinates, drive PWM steering gear to correct ball game picture collected by mobile terminal device by microcontroller;PC end management system is used to receive ball game picture collected by mobile terminal device, and upload to server end for user to pull stream and watch.The application can realize the intelligent live broadcast of basketball event, and the identification process is accurate and efficient, flexible to use and low in cost, with wide application prospect and commercial value.

The invention discloses a method for filtering webpage access based on a kernel driver, which belongs to the technical field of internet communication and comprises the following steps: step 1, a user inputs an access website for a user browser to generate a DNS (Domain Name Server) query request message; 2, judging whether a DNS query request message exists in a local DNS cache or not, if yes, obtaining an IP address for access, and if not, executing a step 3; and step 3, sending a query request to a DNS server, constructing a complete DNS query request network packet according to a network protocol standard, capturing all DNS query request network packets sent to the 53 port by a kernel driving program, and then analyzing target domain names of the DNS query request network packets through a DNS protocol. Centralized and automatic management and control are achieved, the system is particularly suitable for scenes such as machine rooms and classrooms needing unified network behavior management, and the operation and maintenance cost is greatly reduced.

The application discloses a structural damage identification method based on a proxy model and an improved covariance matrix adaptive evolution strategy, and relates to the technical field of structural damage identification.The application comprises the following steps: obtaining a structure to be identified, constructing a finite element model of the structure to be identified, and respectively applying excitation to the structure to be identified and the finite element model to obtain a data set; a hybrid network model based on a convolutional neural network and a long short-term memory network is constructed, and the data set is used for training to obtain a proxy model; the proxy model is improved by using a covariance matrix adaptive evolution strategy based on a model gradient to obtain an optimal solution; a variational Bayesian model correction method is used to correct the optimal solution to obtain the most possible value of a structural damage geometric size parameter, so that damage geometric size and boundary information of the structure to be identified are determined.The application can efficiently and accurately identify structural damage geometric size information.

The embodiment of the invention provides a video encoding and decoding method and device, a computer readable medium and electronic equipment. The video decoding method comprises the following steps: determining a plurality of pixel regions in a current frame based on a preset pixel region size, wherein each pixel region comprises at least one pixel; determining a skipped area in the current frame according to whether each pixel area is processed in a skipped mode or not; and generating reconstruction data corresponding to the current block according to the position relationship between the current block to be decoded and the skipping region. According to the technical scheme of the embodiment of the invention, the coding and decoding efficiency can be improved, and the coding and decoding complexity can be reduced.

This invention discloses a method, system, device, and medium for identifying virtual location vulnerabilities on iOS devices. The method includes the following steps: invoking an iOS application to perform a location request operation; in response to the location request operation, obtaining partial callback location data; generating a first vulnerability identification result based on the data parameters of the partial callback location data; and in response to the first vulnerability identification result being a non-virtual location result, generating a final vulnerability identification result based on the request parameters of the location request operation and the time parameters of the partial callback location data. This invention can more accurately identify the GPX virtual location method on Apple devices. Through dual identification logic, it can efficiently and accurately determine whether a user has used virtual location, effectively improving the authenticity of the location function and application security of Apple applications, enhancing user experience, and possessing high application value.

The invention discloses an SRv6 network dynamic path optimization method and system fused with fault prediction, and the method comprises the steps: obtaining the real-time performance data and topological structure information of an SRv6 network, and carrying out the abnormality recognition and positioning based on the real-time performance data; constructing a heterogeneous graph comprising a physical topology layer and an SRv6 logic layer; outputting a fault probability prediction value and a potential fault type of each link through a pre-trained link fault prediction model; defining a comprehensive optimization cost function, and calculating an optimal main path and an optimal backup path based on the comprehensive optimization cost function; obtaining a corresponding Segment list, and issuing the Segment list to a source node to realize switching of traffic to a new path; and evaluating the real-time performance of the new path, and feeding back evaluation result data to the link fault prediction model for iterative training of the link fault prediction model. According to the scheme, the link fault is predicted by sensing the network state and the pre-training model in real time, and conversion from passive response to active fault avoidance is achieved.

The application discloses a bearing fault classification method and related device. The method comprises the following steps: inputting a first vibration signal collected under a plurality of known fault types of a bearing into a preset dictionary learning algorithm model after processing, and constructing a sparse dictionary containing a plurality of fault type training samples; processing a second vibration signal collected for fault classification to obtain a test sample, performing sparse optimization solving on the test sample, and obtaining a first sparse coefficient; respectively reconstructing the first sparse coefficient and the training sample under a plurality of fault types, and obtaining a plurality of fault type corresponding reconstruction signals; comparing the test sample with the plurality of fault type corresponding reconstruction signals, and determining the fault type corresponding to the test sample according to the comparison result. The application can accurately and effectively realize bearing fault classification diagnosis.

The invention discloses a multi-stage text irrigation recognition method and system based on rules and deep learning, a medium and a product, and relates to the technical field of natural language processing, and the method comprises the steps: carrying out the preprocessing of a target recognition text, and obtaining an intermediate text; performing rapid screening on the intermediate text based on a preset rule, and judging whether the screening is passed or not; if not, it is judged that irrigation exists; if yes, performing disordered word order detection on the intermediate text to obtain a word order score; according to the word order score and a preset word order score threshold value, whether the word order disorder problem exists in the intermediate text or not is judged; if not, it is judged that irrigation does not exist; if yes, inputting the intermediate text into a preset irrigation detection model for irrigation detection to obtain an irrigation probability; judging whether the irrigation probability is greater than a preset probability threshold; if yes, judging that irrigation exists; if not, it is judged that irrigation does not exist. According to the method, the overall detection efficiency is remarkably improved, and efficient and accurate recognition of the text irrigation behavior is realized.

This invention relates to the field of optical component inspection technology, specifically disclosing a method and system for detecting prism manufacturing defects based on contour feature matching. The method includes: acquiring a surface image of the target prism, sequentially performing grayscale and binarization segmentation to obtain a binarized prism image; extracting the original contour point set through contour tracking; applying multi-level Gaussian filtering to the point set to calculate curvature characterization values, thereby segmenting the original contour point set into a straight line segment contour subset and a corner point contour subset; establishing straight line feature descriptors and corner point feature descriptors in parallel, and concatenating the features to obtain a contour feature vector; simultaneously acquiring the theoretical contour feature vector, comparing the differences between the two item by item to identify abnormal edge length regions and abnormal edge angle regions; finally, integrating the spatial locations of these two types of abnormal regions to generate a manufacturing defect distribution map, thereby marking the defect location and defect type of the target prism; this invention can improve the accuracy of prism manufacturing defect detection.

This invention primarily relates to the field of neural network technology. It discloses a method, device, and medium for recognizing traditional Chinese medicine (TCM) decoction pieces based on dynamic serpentine convolution. The method includes: acquiring an image of TCM decoction pieces and inputting it into a preset feature extraction network, which includes multiple convolutional kernels; adjusting a target convolutional kernel among the multiple convolutional kernels to adaptively align the sampling points of the target convolutional kernel along the meandering geometric contour in the TCM decoction piece image; extracting features from the adaptively aligned meandering geometric contour to obtain target features; classifying and recognizing the target features using a preset classifier, and outputting the recognition result of the TCM decoction piece type. This application effectively solves the problem of mismatch between the fixed geometric structure of standard convolutional kernels and the features of the decoction piece image, thereby significantly improving the recognition accuracy and efficiency of TCM decoction pieces.

The invention provides a cable three-dimensional imaging method based on tensor coupling and physical constraint, and the method comprises the steps: carrying out the tensor decomposition of terahertz time-domain spectral data and X-ray projection data of a cable, and obtaining a core tensor and a modal basis matrix; registering terahertz three-dimensional imaging data and X-ray three-dimensional imaging data of the cable based on the core tensor and the modal basis matrix; according to the registered terahertz three-dimensional imaging data and the registered X-ray three-dimensional imaging data, generating three-dimensional potential distribution of the cable by using a pre-constructed joint optimization objective function for physical constraint; and based on the three-dimensional potential distribution, generating a dynamic weight through a double-branch convolutional network, and according to the dynamic weight, performing restoration by adopting a weighted difference value and a context sensing network to obtain a three-dimensional image of the cable. Therefore, deep collaborative information among different modal data is fully mined, and the structural integrity and detail definition of the image are remarkably enhanced.

The application relates to the technical field of artificial intelligence, and provides a method and device for analyzing SIP behavior based on real-time traffic, equipment and a medium, which can adopt a non-intrusive monitoring mechanism, passively copy target SIP messages of a target network by using a traffic capturing module deployed on a network edge device, realize non-intrusive low-delay monitoring of the SIP messages, call a SIP protocol stack to analyze the target SIP messages, quickly extract core metadata, call a rule engine and an abnormal SIP behavior detection model pre-trained based on a machine learning model to perform parallel detection on target SIP features, obtain a target abnormal score, and generate a target response strategy according to the target abnormal score, so that the rule engine and the machine learning model are combined to realize efficient and accurate identification of abnormal SIP behavior.

The present disclosure relates to a test question correction method and device, electronic equipment and storage medium. The test question correction method comprises: obtaining a to-be-corrected image, wherein the to-be-corrected image comprises a handwritten answer of a target test question; predicting the handwritten answer by using a pre-trained prediction model to output a predicted character; determining a target character in the predicted character according to a preset rule; and comparing the target character with a standard answer of the target test question to complete the correction of the target test question. The present disclosure can be applied in a recognition scene with erasing traces, and can efficiently and accurately recognize the handwritten answer in the image.

The invention relates to a sustainable Internet of Things equipment identification method and system based on traffic time sequence characteristics, and the method comprises the steps: capturing traffic data packets of Internet of Things equipment according to a set time interval, and carrying out the feature extraction of each traffic data packet, and obtaining a time sequence characteristic construction data set; constructing an Internet of Things equipment identification model, and training by using the data set to obtain an Internet of Things equipment identification deployment model; obtaining the time sequence characteristics of the newly-added Internet of Things equipment to obtain a newly-added data sample and a new data set; performing continuous comparative learning based on the new data set by using parameters of the deployment model to obtain an updated deployment model; inputting the to-be-identified Internet of Things equipment into the updated deployment model, and outputting to obtain an identification result; the efficient and accurate identification of the Internet of Things equipment is realized by using the time sequence characteristics of the traffic, the sustainable identification of the Internet of Things equipment is realized by using the continuous comparison learning framework, the types of the newly added equipment are accurately classified, and the identification accuracy of the known equipment is kept.

This invention discloses a high frame rate rendering and parsing editing system and device for PDF documents, comprising: a file list upload module, which uploads PDF files and displays a version history list and information; a document parsing logic module, which reads and parses document information, determines the block-level order of the obtained data, deletes useless elements, and sorts and assembles the content according to the layout; and a PDF original document display module, which performs the following operations on the uploaded original document: displaying the PDF file title, cropping the file display page, generating a file directory, and displaying the document parsing results. The file directory generation operation captures the multi-level numerical numbering of the document, classifies the numbering type according to the matching results of the capture groups in the regular expression, and then processes the numbering according to the specified hierarchical mapping rules to finally obtain the file directory numbering. This invention can effectively solve the problems of inaccurate parsing, low editing efficiency, and poor professional adaptability of traditional tools.

This utility model provides a device for a hook-and-unhook robot to detect gaps in a train car. The device includes a base plate disposed at the end of the robot's arm. A disk is fixed to the side of the base plate away from the robot body, and a hook-and-unhook gripper is mounted on the disk surface away from the base plate. Four laser sensors for detecting gaps in the train car are detachably mounted on the disk. These laser sensors are arranged in a square around the hook-and-unhook gripper. A locking component is provided on the disk to lock the laser sensors in their relative positions. By using the laser sensors arranged around the hook-and-unhook gripper on the disk, the gaps in the train car can be accurately and efficiently identified, ensuring smooth hook-and-unhook operation and preventing the hook-and-unhook gripper from colliding with and damaging the train car. Furthermore, the locking component allows for quick disassembly, maintenance, or replacement of the laser sensors.

The invention discloses a product recommendation method and device based on project planning, equipment, a medium and a product, and is applied to the technical field of financial information, and the method comprises the steps: monitoring whether user behavior data of a user to which a project belongs meets a preset push condition or not; if yes, performing multiple rounds of dialogues with the user to which the project belongs based on the dialogue model, and performing project planning demand intention identification; under the condition that the project planning demand intention is identified, generating a questionnaire guide dialogue based on a dialogue model, so that a user to which the project belongs fills a project questionnaire based on the questionnaire guide dialogue; the project questionnaire is analyzed based on the project planning model, and a project planning strategy corresponding to the project questionnaire is generated; calculating the feature similarity between the project planning strategy and the candidate recommended products based on the product recommendation model, and screening out a target product based on the feature similarity; and based on the dialogue model, performing a dialogue of recommending the target product with the user to which the project belongs. The user experience and the product recommendation accuracy can be improved.

The application provides a steel coil number recognition method and system based on DBNet and CRNN. The steel coil number recognition method based on DBNet and CRNN comprises the following steps: acquiring a steel coil image; using a DBNet model to extract a target frame region of a steel coil number in the steel coil image, and returning coordinate information corresponding to the target frame region; cutting the steel coil image according to the coordinate information to obtain a regional image of each steel coil number; taking each regional image obtained by cutting as input, and using a CRNN network model to recognize the character sequence of the number text. The steel coil number recognition method provided in the embodiment of the application can realize automatic, efficient and accurate steel coil number extraction and recognition, and is suitable for steel coil related automatic processing and management scenarios.

The application provides an evaluation method for the closeness of personnel in a human relationship system, comprising: for each pair of related involved objects in an involved object set, establishing a human relationship graph network with a first involved object as the center; determining whether a second involved object is associated with the first involved object; determining the closeness distribution information of the first involved object and the second involved object; expanding the human relationship graph network based on the closeness distribution information; triggered by new data, updating the closeness distribution information between the objects in the human relationship graph network and the associated personnel involved in the new data in real time and dynamically according to a preset closeness calculation model; and determining the human relationship characteristics of any two involved objects in the involved object set. The technical scheme can efficiently and accurately identify the association relationship between the involved object sets on the basis of dynamically updating the closeness between the involved objects.

In the AI training and detection method for identifying the cell-derived species, a microscopic examination sample image A comprises a cell type A image of a species A; the microscopic examination sample image B comprises a cell type B image of a species B; annotating the cell type A image to obtain a cell type annotated image A of the species A; annotating the cell type B image to obtain a cell type annotated image B of the species B; carrying out AI training by using the cell labeling image A and the cell labeling image B to obtain an AI species cell characteristic data set; and the AI species cell characteristic data set is combined with the corresponding AI algorithm module, and has the capability of identifying and distinguishing the cells of the species A and the cells of the species B. The microscopic examination sample image is recognized through an AI recognition algorithm, and cell source species in the sample are recognized through the AI recognition algorithm according to the AI species cell feature data set; the AI species cell characteristic data set is obtained by training labeled cell pictures, and the cell pictures are derived from two or more species.