Student Mental Health Cloud Assessment Algorithm Based on Blink Frequency Image Detection Algorithm in Heterogeneous Network Environment

Abstract

With the development of society, the environment that contemporary college students live in becomes more and more complex, and the mental health of college students has become a very concerned issue at the social level. This paper firstly introduces the relationship between blink frequency and college students' mental health, and uses the blink frequency image detection algorithm to evaluate college students' mental health based on complex heterogeneous networks. Then use C++ to design a cloud evaluation platform for students' mental health in a heterogeneous network environment, upload the evaluated mental health data to the cloud platform based on big data, and use cloud evaluation algorithms to comprehensively review the mental health of college students. Finally, a joint ranking model is used. "MutuRank" tests the mental health intelligence evaluation index of college students. The results show that the method can comprehensively and objectively describe the change characteristics of college students' mental health, and the results of the intelligent assessment of college students' mental health are stable.