In the intelligent classroom,it is of great significance to grasp the emotional state of student in real time for improv-ing the quality of teaching and personalized education.The channel attention mechanism is introduced to improve the VGG16 con-volutional neural network.Combined with the multilayer perceptron the VGG16_SE_MLP model is proposed for the classification and recognition of student micro-expression and emotion assessment.Firstly,the micro-expression dataset is preprocessed,then the feature is extracted,and the SE module is introduced behind the convolution layer,and the batch normalization layer is added to prevent overfitting;the extracted features and micro-expression class are calculated layer by layer through MLP;finally,the student emotion is evaluated.Experimental results show that the proposed method performs well in micro-expression classification and emo-tional assessment,providing a new idea for intelligent classroom.
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