Facial expression recognition based on VGG16 and attention mechanism

In order to address the issues of low accuracy and limited generalization ability in current facial expression recognition, a facial expression recognition model based on VGG16 and attention mechanism is proposed.The proposed model is based on VGG16 and embeds Switchable Normalization layers and SE channel attention mechanism modules into the network,enabling the model to dynamically select weights for different normalized operation and channels.Additionally,the dataset is subjected to various image preprocessing techniques such as rotation and horizontal flipping.Experimental results demonstrate that the proposed model achieves an impressive accuracy rate of 73.22% on the FER2013 dataset,which outperforms many existing mainstream methods and achieves good performance in facial expression recognition.