Open AccessDesign and implementation of face recognition system based on convolutional neural network
Author(s) -
Yilong Ma,
Huajun Wang,
Jun Wan,
ZhenHeng Wang,
Yongyi Yang,
Chuanfeng Huang
Publication year - 2021
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 - 10.1088/1742-6596/2029/1/012096
Subject(s) - convolutional neural network , computer science , facial recognition system , adaptability , artificial intelligence , python (programming language) , face (sociological concept) , deep learning , flexibility (engineering) , pattern recognition (psychology) , artificial neural network , machine learning , speech recognition , ecology , social science , statistics , mathematics , sociology , biology , operating system
The main features of face recognition are easy to use, quick to update, high flexibility, high accuracy, high environmental adaptability and so on. This passage of facial recognition technology based on convolutional neural network, which combines the present popular Python and Opencv Keras to identify development system, will make face recognition more efficient and more intelligent. And convolutional neural network based on face recognition data can improve accuracy and reduce the error rate through training. This experiment makes efforts to perfect the training model and enhance the influence of face recognition, so it could be more influential and smarter in higher precision applicable areas.