A Facial Expression Recognition Algorithm Based on Optimized ResNet
Aiming at the problems of low accuracy of traditional facial expression recognition algorithms and many network pa-rameters,a facial expression recognition algorithm based on optimized residual network is proposed.Firstly,two standard convolu-tion layers are used to extract the shallow features of facial expressions.Then,the depth separable convolution hybrid channel atten-tion mechanism is used to improve the residual network to extract the deep features of facial expressions.Finally,softmax function is used to classify the extracted features.Experiments on the public dataset FER2013 and CK+for facial expression recognition show that the classification accuracy is 70.57%and 99.28%respectively.Experimental results show that the algorithm performs well,the network has strong generalization ability,and can play a good role in facial expression recognition in complex situations.
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