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Issue title: Fuzzy System for Economy Back on Track
Guest editors: Anand Paul, Simon K.S. Cheung, Chiung Ching Ho and Sadia Din
Article type: Research Article
Authors: Liu, Nan; * | Liu, Haihong | Liu, Haining
Affiliations: Psychology Department, Chengde Medical University, Chengde, Hebei, China
Correspondence: [*] Corresponding author. Nan Liu, Chengde Medical University, Chengde, Hebei, China. E-mail: [email protected].
Abstract: In recent years, college campus incidents caused by mental health problems have been increasing year by year, and college students’ mental health problems have become the focus of attention of schools, society and parents. Based on this, this paper proposes a facial emotion recognition method for college students. By using moving target detection, target classification, target tracking, and a series of image preprocessing techniques, this method achieves intelligent monitoring of the area where college students are located and can automatically alert when a potentially dangerous target is found. Moreover, this method uses a combination of shape features and motion features to select and extract feature quantities. In addition, the method calculates the similarity between the target and candidate target corresponding sub-models, and according to the ability of each feature to distinguish between the target and the background, monitors the student’s mental health in real time and prevents various problems from occurring. Through experimental research, we can see that the model constructed in this paper has good performance.
Keywords: Facial recognition, neural network, college students, mental health
DOI: 10.3233/JIFS-189536
Journal: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7061-7072, 2021
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