Oral mucosal disease recognition based on dynamic <scp>self‐attention</scp> and feature discriminant loss

Abstract

Convolutional neural networks can effectively capture the visual features of the oral mucosal disease lesions, and the distinguished visual features of different oral lesions can be extracted better using dynamic self-attention and feature discrimination loss function, which is conducive to the auxiliary diagnosis of oral mucosal diseases.