9results about How to "Solve data redundancy" patented technology

The embodiment of the invention discloses a wafer test result generation method and device, electronic equipment and a storage medium, and relates to the technical field of semiconductor chips, and the method comprises the steps: obtaining a plurality of test files generated by carrying out multiple tests on the same wafer; integrating the plurality of test files, and only reserving an optimal test result for a plurality of test results of the same semiconductor chip on the wafer; and obtaining a final test result of the wafer based on the integrated test file. The technical scheme provided by the embodiment of the invention can be suitable for a wafer test scene, and can solve the problems of low wafer test data processing efficiency and inaccurate test result extraction in the prior art.

The invention discloses an in-network cache-driven active network telemetering scheme. The scheme comprises the following steps of: storing and multiplexing network information collected by a telemetering probe by using a designed cache strategy; the data transmission quantity from the data plane to the controller is reduced by using an incremental transmission technology; and finishing planning oriented to the path of the cache probe in the network by using deep reinforcement learning based on an attention mechanism. According to the method provided by the invention, the data transmission quantity from the data plane to the controller can be greatly reduced, and the control overhead is also remarkably reduced.

The present application relates to the field of wisdom agriculture and image recognition technology, specifically to a crop disease and pest monitoring system based on image recognition, comprising: an environment perception module, which obtains the environmental context parameters of the monitoring area through multi-modal sensor nodes; a multi-source context analysis module, which constructs a disease and pest outbreak risk model in combination with historical disease and pest distribution spatio-temporal data and calculates the disease and pest risk level; an adaptive strategy generation module, which dynamically reconstructs the image acquisition mode and feature extraction strategy according to the risk level and the edge side resource constraint state, and generates adaptive perception instructions; an image acquisition execution module, which adjusts the physical acquisition parameters and algorithm calculation density of the visual sensor in response to the instructions, and executes image acquisition and recognition; the present application breaks the traditional rigid acquisition mode and realizes the optimal balance between monitoring efficiency and device survival period.

The invention discloses a blacklist data processing method, system and device and a readable storage medium, reprocessing full-amount blacklist data processed by a preset AI model in a data warehouse, determining incremental blacklist data, and directly synchronizing the incremental blacklist data to a blacklist system according to a preset period by the data warehouse. The situation that one more data is stored through a risk control system in the middle is avoided, and system calling links are reduced; furthermore, the blacklist system can be compared with the data volume of the data warehouse based on each scheduling, whether the problem of number leakage exists or not is searched, in addition, a data compensation processing mechanism is further provided, number complementation is flexibly carried out, and the efficiency is improved. The problem of resource waste caused by full data synchronization and the problem of data redundancy caused by the fact that multiple systems store the same data in an existing scheme are solved.

This invention discloses a SPAD sparse 3D ranging system and method based on near-pixel end sensing. The system includes: a photon counting circuit for accumulating the number of photon event pulse signals output by SPAD pixels and outputting a two-dimensional intensity image; a ROI extraction circuit for obtaining a binary ROI image based on an adaptive threshold conversion; a morphological filtering circuit for filtering and ROI fusion operations on the binary ROI image to generate an ROI mask; a reconfigurable connection network for dynamically establishing electrical connection paths between SPAD pixels within the ROI mask and the corresponding TOF extraction circuits; and a TOF extraction circuit for acquiring the TOF results of SPAD pixels within the ROI mask and outputting a sparse 3D image. This invention reduces the number of spatial scans required for a single frame image and solves the data redundancy problem caused by traditional SPAD LiDAR outputting full-resolution 3D images.

The invention discloses a method and system for repairing automobile software defects, and relates to the field of vehicle-mounted computers.The method comprises the steps that when it is determined that automobile software is in a to-be-repaired state based on a software running log, a software repairing task including software version information and a repairing task ID is generated; sending the software repair task to the user terminal, so that the user terminal obtains repair resources from the remote server when the network environment meets a preset network condition; after resource acquisition completion information returned by the user terminal is received, acquiring repair resources from the user terminal; after the integrity verification of the repair resource is successful, running a software installation update program based on the repair resource; after the restoration resources are loaded, restoration feedback information and vehicle self-inspection information are collected and sent to the user terminal, so that the user terminal uploads the restoration feedback information and the vehicle self-inspection information to the remote server. By implementing the method, software defect repair can be provided when the vehicle is located in an area with unstable network connection.

The invention discloses a traffic scene-oriented hyperspectral hybrid expert adapter target tracking method and system, and belongs to the technical field of hyperspectral visual target tracking. The method comprises the following steps: firstly, preprocessing a hyperspectral vehicle tracking video sequence, dividing a hyperspectral channel into multi-stream groups, performing dynamic cutting and patch embedding, and constructing a multi-stream image token sequence; then, a hyperspectral interaction hybrid expert tracking network comprising a multi-stream Transform extraction module, a hybrid expert adapter and a time-space hidden state token evolution mechanism is introduced, and joint modeling is carried out on hyperspectral features of a multi-stream template image and a search area image; further, adaptive enhancement is performed on the multi-dimensional features and background interference is suppressed through a mixed expert module consisting of a spectrum expert, a space expert, a time expert and a visual expert; and finally, target positioning prediction is executed based on the enhanced features, and a target tracking result is output. The method can effectively mine interaction information between hyperspectral bands, realizes robust target tracking in combination with a spatio-temporal context, and is suitable for vehicle target tracking application in a complex traffic scene.

The application discloses a low-voltage area distribution network fault diagnosis method based on light storage equipment trusted access, and belongs to the technical field of power grid fault diagnosis. The steps comprise the following: in a trusted computing environment constructed by a security chip, a protocol deep analysis is performed on a data packet of a light storage equipment to obtain trusted standardized data; a minimum feature subset required for fault diagnosis is dynamically selected based on a maximum correlation minimum redundancy algorithm, and encrypted transmission is collected to obtain efficient sensing data; the efficient sensing data is fused with historical fault cases to construct an edge fault diagnosis knowledge unit; when a fault occurs, the edge fault diagnosis knowledge unit is used to perform parallel execution of fault type rapid identification and power supply recovery potential pre-evaluation. The application adopts protocol deep analysis and a trusted computing environment, can ensure the integrity and security of non-standard access data, and dynamically optimizes the dimension of measurement data through a maximum correlation minimum redundancy algorithm, thereby improving the real-time performance and efficiency of fault type rapid identification and power supply recovery potential pre-evaluation.

The invention belongs to the field of array antenna signal processing, and particularly relates to a low-complexity dimensionality reduction preprocessing method and a direction of arrival estimation method based on a sparse array, which are characterized in that a bijection transformation matrix is constructed through a mapping relation between a physical array and a virtual array; according to the method, the virtual array single-block beat data is directly constructed by constructing the bijection transformation matrix of the sparse physical array and the virtual array, so that the problem of resource waste caused by data redundancy in a covariance matrix in a traditional method is solved, and the method has the advantages of being simple in structure, convenient to operate and high in practicability. And technical support is provided for engineering implementation of the direction of arrival.