The invention discloses an
artificial intelligence assisted
peptic ulcer combined hemorrhage endoscopic
risk assessment network and model, the assessment network is a classification network, the classification network comprises more than one double-
branch module, the double-
branch module divides an input feature into two branches to be processed respectively, and the two branches are connected with each other. One
branch extracts local features of the image through
convolution operation, the other branch extracts global spatial features of the image through depth separation
convolution, different normalization methods are adopted for the two branches, the
convolution branch adopts batch normalization operation, and the depth separation convolution branch adopts layer normalization operation; a compression-incentive attention module is embedded in the output end of each branch, so that the classification network can adaptively enhance respective important feature channels in the two branches, and then channel splicing is performed to fuse the features of the double branches. The classification network can well perform
peptic ulcer combined bleeding
endoscopic image feature extraction.