Face Recognition Using Convolutional Neural Networks
Conference: ICMLCA 2021 - 2nd International Conference on Machine Learning and Computer Application
12/17/2021 - 12/19/2021 at Shenyang, China
Proceedings: ICMLCA 2021
Pages: 5Language: englishTyp: PDF
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Authors:
Wang, Qi (Aliyun School of Big Data, Changzhou University, Changzhou, China)
Yu, Zhenyue (Electrical and Computer Engineering department, Queen's University, Kingston, Canada)
Zhang, Yiting (School of Computer Engineering and Science, Shanghai University, Shanghai, China)
Abstract:
The realization of automatic face image recognition by computers has seen attractive application prospects in the fields of information security, human-machine interaction and monitoring. Studies of face recognition have a significant influence on modern society in that they not only promote the understanding of the human visual system itself but also meet the needs of artificial intelligence applications. Compared with traditional machine learning algorithms, convolutional neural networks (CNN) can yield better performance and higher efficiency in face recognition. In this paper, we illustrate the mechanism of CNN methods, followed by discussions on the latest research progress of face recognition using CNN methods and comparisons between different algorithms. Furthermore, we describe a state-of-the-art CNN model, which takes advantage of the internal and external features of the face.