Design of a Face Recognition System based on Convolutional Neural Network (CNN)

Authors

  • Y. Said Electrical Engineering Department, Northern Border University, Saudi Arabia | Faculty of Sciences of Monastir, University of Monastir, Tunisia http://orcid.org/0000-0003-0613-4037
  • M. Barr Electrical Engineering Department, Northern Border University, Saudi Arabia
  • H. E. Ahmed Electrical Engineering Department, Northern Border University, Saudi Arabia and Faculty of Engineering, Benha University, Egypt

Abstract

Face recognition is an important function of video surveillance systems, enabling verification and identification of people who appear in a scene often captured by a distributed network of cameras. The recognition of people from the faces in images arouses great interest in the scientific community, partly because of the application interests but also because of the challenge that this represents for artificial vision algorithms. They must be able to cope with the great variability of the aspects of the faces themselves as well as the variations of the shooting parameters (pose, lighting, haircut, expression, background, etc.). This paper aims to develop a face recognition application for a biometric system based on Convolutional Neural Networks. It proposes a structure of a Deep Learning model which allows improving the existing state-of-the-art precision and processing time.

Keywords:

face recognition, biometrics, Convolutional Neural Networks (CNNs), artificial intelligence, deep learning

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How to Cite

[1]
Y. Said, M. Barr, and H. E. Ahmed, “Design of a Face Recognition System based on Convolutional Neural Network (CNN)”, Eng. Technol. Appl. Sci. Res., vol. 10, no. 3, pp. 5608–5612, Jun. 2020.

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