9 results about "Membrane computing" patented technology

The application discloses a kind of building contour regularization-oriented polygon generation methods for remote sensing, it is related to remote sensing image recognition technical field, including: through the image instance segmentation model of training completion, real-time high-resolution remote sensing image is carried out sliding window prediction, generates candidate building instance mask, and according to candidate building instance mask calculates center point coordinate and mask area;According to mask area, generate adaptive center point distance threshold, and combine center point coordinate and mask area to exclude duplicate candidate building instance mask;Obtain elevation data that is spatially aligned with real-time high-resolution remote sensing image, carry out spatial superposition calculation to non-duplicate candidate building instance mask and elevation data, obtain elevation statistical characteristics;The application realizes the deduplication processing of candidate building instance mask, and under the unified spatial reference, combine elevation data to complete building floor value calculation and regularized building polygon generation.

The application provides a flame dynamic behavior recognition method based on multi-modal timing modeling, comprising: pre-processing video frames, extracting multi-modal spatial features and spatial detail features; extracting flame edge microscopic dynamic features through a convolutional long short-term memory network, and performing global timing correlation modeling through a transformer network to obtain global features; generating a binary mask of a flame region based on the global features and the spatial detail features; calculating the pixel area of the flame region based on the binary mask, and differentiating the change thereof to obtain a spread rate and an acceleration; constructing a fire situation threat index based on the spread rate and the acceleration, and performing graded early warning of a fire risk. The application has the beneficial effects that the early warning time node is significantly moved forward, the false positive rate of the security system is greatly reduced, scientific data support is provided for fire emergency decision-making, and the accuracy of area statistics and trend analysis is ensured.

This invention discloses an intelligent evaluation method and system for the teaching process based on learning behavior analysis, belonging to the field of intelligent evaluation technology for the teaching process. The method includes: acquiring classroom videos to extract student eye region images and establishing a mapping between time blocks and teaching segments; extracting specular and dark nucleus proxy masks and calculating the symmetrical pupil-occluded specular arc index; calculating the evidence reliability weight and eye region visibility evidence value accordingly; constructing a classroom knowledge graph containing evidence and artifact nodes, and writing the above parameters into the graph; retrieving the evidence set of the target segment, using the reliability weight to weight and aggregate the visibility evidence value to obtain an attention score and generate a traceability link. This invention effectively suppresses polarization screen reflection interference by quantifying physical artifacts and utilizing graph aggregation, achieving interpretability and traceability of the evaluation results.

This application provides a mask layout correction method, system, medium, program product, and terminal based on a combination of membrane computing and the DBSCAN algorithm. The method involves obtaining an initial layout, performing preliminary clustering on the initial layout using a preset clustering method to obtain several partitions and their corresponding density and contour features; obtaining initial density and contour parameters for DBSCAN clustering; iteratively optimizing the initial clustering parameters of the DBSCAN clustering using a preset membrane computing algorithm based on the density and contour features of each partition to obtain the optimal clustering parameters for each partition; performing DBSCAN clustering on each partition based on the corresponding optimal clustering parameters to obtain the core region, boundary region, and sparse region of the initial layout; and correcting the core region, boundary region, and sparse region based on a preset correction strategy to obtain the corrected layout of the initial layout. This improves the accuracy of mask layout correction.

The application provides a FY4B remote sensing single-channel super-resolution reconstruction method based on ESRGAN, which comprises the following steps: analyzing, uniformly cutting, scale constraining and quality detecting the resolution data of FY4B and FY3D to obtain pretreatment data; generating a maximum effective pixel intersection mask according to the pretreatment data; calculating the effective pixel ratio and performing patch screening according to the maximum effective pixel intersection mask to obtain training data; constructing an ESRGAN network structure and performing data reconstruction on the training data to obtain a predicted image. Through the establishment of paired samples of the same day, the uniform cutting alignment and scale constraint, the patch screening and mask loss calculation based on the maximum intersection of effective pixels, and the reconstruction strategy combining pixels, high frequencies and adversarial learning, the FY4B single-channel data is realized from low resolution to high resolution in detail enhancement and structure reconstruction.

The application discloses an ore crushing control method and system, electronic equipment and a readable storage medium. The method inputs a multi-scale feature map fused into a feature mapping layer to obtain a multi-scale fusion feature tensor; inputs the multi-scale fusion feature tensor into a candidate region generation layer to determine a target candidate region; inputs the target candidate region into an instance segmentation layer to determine a target instance segmentation mask; calculates a particle equivalent diameter based on the target instance segmentation mask; determines a medium crushing discharge particle size and a fine crushing discharge particle size under a P80 particle size index according to the particle equivalent diameter; calculates a material instantaneous conveying flow based on a continuous time sequence point cloud volume integration model; performs time integration on the material instantaneous conveying flow to obtain a fine crushing discharge throughput; and performs hierarchical control on ore crushing through the medium crushing discharge particle size, the fine crushing discharge particle size, the fine crushing discharge throughput and a fine crushing machine running power. The application can improve the ore crushing efficiency and the qualified rate of the crushing products.

This invention discloses a method for locating the centroid of a rock block based on instance segmentation and keypoint detection, belonging to the field of visual perception and automated operation of mining robots. First, this invention constructs a dataset for mining rock pile scenarios and annotates and enhances the images. Then, an improved YOLOv8 instance segmentation network is designed to identify multi-target regions in the rock pile images, outputting an instance mask for each rock block. Next, the geometric centroid and effective impact area center of the rock block are calculated based on the instance mask, and centroid keypoint supervision information is generated. Finally, a posture keypoint detection network is trained based on centroid keypoint supervision to achieve end-to-end rapid localization of the rock block's centroid, used for the generation of impact points by the hydraulic breaker arm and operational control. Experimental results show that compared with localization methods based on detection box centers or traditional image processing, as well as the original YOLOv8 segmentation-keypoint baseline method, this invention can significantly improve the accuracy and robustness of centroid localization under complex occlusion and dense stacking conditions.

The present application relates to the technical field of electronic manufacturing visual detection, in particular to a circuit board welding fault identification method and system based on machine vision, the method comprising: receiving a welding area image and completing gray scale conversion, Gaussian filtering and adaptive threshold segmentation, and extracting a solder joint binary mask. The geometric shape parameters of the solder joint are calculated, the ideal state category is judged through a welding state inference model, the deviation vector is obtained by comparing the ideal state and the actual parameters, and the state inversion calculation is started. The process calls a solder flowability physical simulation engine, simulates the solder spreading behavior based on temperature field and pad layout data, iteratively adjusts the surface tension coefficient and wetting angle parameters, and matches the simulation morphology and the actual morphology until the matching parameters are mapped as the welding fault type. The present application improves the attribution accuracy of circuit board welding fault identification through physical cause inversion and simulation parameter iterative matching.