Facial expression recognition via ResNet-50

As one of the most important directions in the field of computer vision, facial emotion recognition plays an important role in people's daily work and life. Human emotion recognition based on facial expressions is of great significance in the application of intelligent human-computer interaction. However, in the current research on facial emotion recognition, there are some problems such as poor generalization ability of network model and low robustness of recognition system. In this content, we propose a method of feature extraction using the deep residual network ResNet-50, which combines convolutional neural network for facial emotion recognition. Through the experimental simulation of the specified data set, it can be proved that this model is superior to the current mainstream facial emotion recognition models in the performance of facial emotion detection.