4results about How to "Solve data redundancy" patented technology

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.

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 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.