Open AccessResearch on Classroom Attendance System Based on Face Recognition
Author(s) -
Jingyu Pu,
Liang Zhang,
Jinqian Zhang,
Xue Ziwei,
Xixin Zhang,
Jie Yang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1616/1/012095
Subject(s) - facial recognition system , computer science , authentication (law) , access control , face (sociological concept) , attendance , artificial intelligence , deep learning , identity (music) , variety (cybernetics) , machine learning , computer security , pattern recognition (psychology) , sociology , social science , physics , acoustics , economics , economic growth
Deep learning face recognition technology has become one of the most popular technologies. The explosive growth in the use of face recognition has brought a variety of practical needs. Face recognition can be applied to identity authentication, bank security, forensic investigation, face scanning payment, access control system and so on. Existing face recognition methods have achieved remarkable results. With the continuous development of deep learning technology, many depth methods show better accuracy than human recognition. Based on the in-depth study and discussion of the deep learning method, this paper applies the theory to practice, and designs and develops a set of face recognition system for classroom attendance.