A study of convolutional neural networks in face recognition
Zhiben Song, Yilun Yu · International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021) · 2022
Face recognition technology has attracted much attention in the past few years because of its potential value of both research and applications in the fields of pattern recognition, image analysis, computer vision and other fields. Meanwhile, as an important branch of the deep learning family, convolutional neural network (CNN) methods has yield remarkable achievements in many large-scale recognition tasks in the field of computer vision, especially face recognition. This is because, compared to classic neural networks, CNN has more hidden layers, a more complicated network topology, and more robust feature learning and feature expression capabilities. This paper gives an overview of the development on face recognition using CNN approaches, including categories of current face recognition technologies, description of the CNN method, and applications and research progress on CNN for face recognition.