Biological Image Processing Algorithm Based on Attention Mechanism and Convolutional Neural Network

Abstract

This paper proposes a model algorithm based on convolutional neural network combined with attention mechanism to realize fast and accurate identification of biological image. Firstly, deformable convolution is used to extract features in the horizontal and vertical directions, respectively. Secondly, attention modules are used to capture remote dependencies in one spatial direction, while accurate position information is retained in another spatial direction, so that information in both vertical and horizontal directions can be retained; after a series of transformations, the attention vector is obtained and multiplied back to the original feature vector as a weight factor. The experimental results show that the proposed algorithm can effectively improve the image quality, improve the image clarity, avoid color distortion, and achieve good results in both synthetic and real low-illumination images, and the subjective and objective evaluation indicators are better than the contrast algorithm.