Application of Convolutional Neural Network in Emotion Recognition of Ideological and Political Teachers in Colleges and Universities

Abstract

With the update of Internet technology and the development of we-media, ideological and political education in colleges and universities has been greatly impacted. Higher requirements are put forward for ideological and political teachers in colleges and universities, whose emotions seriously affect the quality and effect of teaching. Aiming at the problems of poor network generalization ability and large computation amount caused by many network parameters in the existing emotion recognition methods, a face emotion recognition method based on convolutional neural network is proposed. The network structure of nested Maxout multilayer perceptron layer is constructed by optimizing the convolutional neural model. Maxout can enhance the feature extraction capability of the convolutional layer of convolutional neural network. Meanwhile, Maxout performs linear combination of target features to select the most effective feature information. Then, the pretraining model is used for emotion recognition training. The strong perception ability of the model for facial features is retained by changing the important parameters. Simulation results demonstrate that this method has a higher recognition rate of face emotion and can effectively achieve accurate face emotion classification.

DA-CNN-Driven Innovative Ideological Politics Education Management System

“…At present, with the emergence and wide application of various new technologies such as the Internet, cloud computing, big data, and arti cial intelligence [1][2][3][4][5][6][7][8][9], the environment faced by ideological and political management is becoming more and more complex, which puts forward new requirements for ideological and political management and gives birth to new changes in ideological and political education and management in the new era [10][11][12][13][14][15]. erefore, in the era of big data, the reform and innovation of ideological and political management are imminent [16][17][18].…”

Unmasking the challenges in ideological and political education in China: A thematic review

“…Some scholars focused on creating a platform for collaborative creation for ideological and political science teachers, integrating resources, and advancing scientific research and instructional support. In response to the greater demands of ideological and political teachers [ 3 ], while some suggested a convolutional neural network-based emotion identification approach for precise facial emotion categorization, assisting teachers in concentrating on teaching efficacy from an emotion management viewpoint [ 52 ].…”

Face Recognition Model Design Based on Convolutional Neural Networks

“…e main principal of convolutional neural network is the face feature extraction and the training of neural network model, so the structure of convolutional neural network will determine the effect of face recognition behind [15][16][17][18][19][20][21][22][23][24][25][26][27][28]. e convolutional neural network system has designed eight layers of neural network, including three convolutional layers, three pooling layers, one fully connected layer and one output layer.…”