The invention relates to the technical field of
lesion recognition, solves the technical problem that details in an image cannot be accurately recognized in the prior art, and particularly relates to a method for recognizing a
leukoplakia vulvae
lesion image, which comprises the following steps of: S1, acquiring a
leukoplakia vulvae
lesion image at a # imgabs0 # moment, performing primary
processing on the focus image to obtain a first
processing value # imgabs1 #; and S2, calculating a second
processing value # imgabs3 # of the lesion image at the # imgabs2 # moment, and fusing the first processing value # imgabs4 # and the second processing value # imgabs5 # to obtain a preprocessed image. According to three-value positioning of the to-be-processed image, classification of pixels in the to-be-processed image can be completed according to a query value, a key value and a positioning value, the fine-grained extraction capability is improved by means of
convolution and an attention mechanism, and the accuracy of the fine-grained extraction is improved. Meanwhile, the parameter number of the model can be optimized, the model operation recognition efficiency is improved, and the accuracy and the recognition speed of focus position recognition in the to-be-processed image can be improved by combining the average
pooling mode with the classification threshold value.