FACIAL EXPRESSION RECOGNITION METHOD BASED ON MULTI-CHANNEL RESIDUAL NETWORK
To solve the problem of insufficient feature extraction of CNN in complex images,an improved residual network based on attention is proposed for facial expression recognition.A dual stream network was designed to detect the key points while completing the coarse feature facial expression recognition,and the attention mechanism was used to increase the weight of the features around the key points.Based on the residual network model,the jump connection between residual blocks was improved,and the ordinary convolution in residual blocks was improved to block convolution to enhance the feature extraction ability.Two facial expression recognition networks were combined for classification.The experimental results show that the model scheme has better performance.
国家科技期刊平台
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