Reports from Anyang Normal University Add New Data to Research in Computational Intelligence and Neuroscience (Study of Multiscale Fused Extraction of Cropland Plots in Remote Sensing Images Based on Attention Mechanism)

摘要

By a News Reporter-Staff News Editor at Robotics Machine Learning DailyNews Daily News – New research on computational intelligence and neuroscience is the subject of a newreport. According to news reporting originating from Anyang, People’s Republic of China, by NewsRxcorrespondents, research stated, “Cropland extraction from remote sensing images is an essential part ofprecise digital agriculture services.”Funders for this research include National Natural Science Foundation of China.The news journalists obtained a quote from the research from Anyang Normal University: “This paperproposed an SSGNet network of multiscale fused extraction of cropland based on the attention mechanismto address issues with complex cropland feature types in remote sensing images that resulted in blurredboundaries and low accuracy in plot partitioning. The proposed network contains different modules, suchas spatial gradient guidance and dilated semantic fusion. It employs the image gradient attention guidancemodule to fully extract cropland plot features. This causes the feature to be transferred from the encodinglayer to the decoding layer, creating layers full of key features within the cropland and making the extractedcropland information more accurate. In addition, this study also solves the problem caused by a largeamount of spatial feature information, which losses easily during the downsampling process of continuousconvolution in the coding layer. Aiming to solve this issue, we put forward a model for consensus fusion ofmultiscale spatial features to fuse each-layer feature of the coding layer through dilated convolution withdifferent dilated ratios.”