Investigation of a novel approach to facial emotion detection using an attention-enhanced residual network

This paper introduces a facial expression recognition method based on a residual network that incorporates a channel-space attention mechanism module. The method enhances the ResNet50 architecture and integrates label smoothing as a regularization technique. These innovations effectively reduce the impact of noise in facial expression recognition tasks, improve the model's generalization ability, and significantly boost recognition accuracy.