Abstract

Abstract This paper first constructs an intelligent education management system for universities according to their needs and explains its logical and technical architecture. Secondly, a multi-task convolutional neural network with MTCNN is used to detect faces, and different loss functions are selected to ensure recognition accuracy. Finally, the effectiveness of the application of intelligent education management systems in universities is verified through performance tests. The results show that the time consumed for face recognition detection using MTCNN is 524ms, and the response time of each function of the system does not exceed 500ms when the number of concurrent users is less than 500, which indicates that the intelligent education management system based on MTCNN face recognition algorithm has a good response speed and meets the requirements of intelligent education management in colleges and universities.

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