Author(s)

Qiu Haijing, Li Dan*, Zhang Kewen, Shi Yu, Chen Wen, Fan Shukang

Affiliation(s)

Xuzhou University of Technology, Xuzhou, Jiangsu, China.

Corresponding Author

Li Dan, email: 3376486524@qq.com

ABSTRACT

Facial expression is an important indicator to reflect human external performance and internal emotions and their changes. Studies have shown that facial expressions are the most commonly used and the most efficient method among the three ways of human dissemination of information: action, dialogue and expression. With the progress of the times and the development of society, artificial intelligence has gradually changed from theoretical scientific research to practical application into human daily life. The facial expression classification system in this paper uses the Python programming language combined with the Pycharm integrated development tool to develop the system, uses OpenceCV to preprocess the image, uses the Pytorch deep learning framework to build and train various neural network models, and combines Visdom to achieve data visualization.

KEYWORDS

Face recognition; expression recognition; cnn.

CITE THIS PAPER

Qiu Haijing, Li Dan, Zhang Kewen, Shi Yu, Chen Wen, Fan Shukang. Research and implementation of face expression recognition and classification based on CNN. Journal of Computer Science and Electrical Engineering. 2022, 4(1): 1-7.

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