3results about How to "Improve capture sensitivity" patented technology

This invention discloses a method and system for detecting solder joints on PCB circuit boards based on image recognition, belonging to the field of image processing technology. The method first acquires and preprocesses 3D point clouds of PCB solder joints, and calculates the local geometric probability density. Non-uniform downsampling is performed using density inverse weighting, prioritizing the retention of sparse key features such as solder joint pins and removing redundant substrate data, outputting a set of physical feature points. This set is then input into a feature extraction network, and strong correlations in feature dimensions are eliminated through local and global forging mapping technology to construct isotropic hypersphere spatial feature vectors. Finally, a multi-coverage discrimination model containing defective hyperellipsoids and normal hyperspheres is constructed based on local density and spatial features. The solder joint quality is comprehensively judged using an integrated voting strategy. This invention effectively solves the problems of false detection and missed detection caused by sparse feature loss and sample imbalance, and significantly improves the detection accuracy of minute defects.

This invention relates to the field of medical assistance technology, specifically to a pneumonia medical assistance system based on an improved VMamba model. The system includes: dividing the lung image to be diagnosed into raster cells based on a raster cell partitioning algorithm; calculating the lesion representation coefficient of each raster cell within each management time period; calculating the lesion representation index of the lesion trend path within the management period based on the raster cells along the lesion trend path; determining whether the raster cells covered by the lesion trend path are lesion regions based on the lesion representation index; inputting the lung field feature map and semantic feature vector into the improved VMamba model after channel-level concatenation, and outputting the pneumonia classification diagnosis result; and linking the pneumonia classification diagnosis result with a pneumonia knowledge graph to generate a visual auxiliary diagnosis report, significantly improving the accuracy and stability of lung medical image processing and achieving full-process automation of intelligent image analysis.

This invention belongs to the field of parameter optimization technology, specifically relating to a method and system for optimizing parameters in high-pressure gas detection and testing. The method includes: simultaneously collecting pressure and temperature data from upstream and downstream nodes of a pipeline to construct thermodynamic-pressure coupling characteristics, and extracting a spatiotemporal turbulence calibration factor using physical delay alignment; subsequently, calculating pipeline turbulence dissipation indices based on this calibration factor, and generating dynamic pressure compensation weights based on an explosion-proof safety boundary mechanism; finally, adaptively weighting the pressure sequence and fusing it with temperature features, inputting the results into a deep neural network to output the final optimized parameters. This invention can effectively eliminate spurious interference from spatially propagated waves, capture the true fluid state, prevent the risk of overpressure rupture, and improve the safety and accuracy of automated high-pressure detection and control systems.