Face Recognition System based on Convolution Neural Networks
Автор: Htwe Pa Pa Win, Phyo Thu Thu Khine, Khin Nwe Ni Tun
Журнал: International Journal of Image, Graphics and Signal Processing @ijigsp
Статья в выпуске: 6 vol.13, 2021 года.
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Face Recognition plays a major role in the new modern information technology era for security purposes in biometric modalities and has still various challenges in many applications of computer vision systems. Consequently, it is a hot topic research area for both industrial and academic environments and was developed with many innovative ideas to improve accuracy and robustness. Therefore, this paper proposes a recognition system for facial images by using Deep learning strategies to detect a face, extract features, and recognize. The standard facial dataset, FEI is used to prove the effectiveness of the proposed system and compare it with the other previous research works, and the experiments are carried out for different detection methods. The results show that the improved accuracy and reduce time complexity can provide from this system, which is the advantage of the Convolution Neural Network (CNN) than other some of the previous works.
Biometric Modalities, Computer Vision, Convolution Neural Network, Deep Learning, Face Recognition, FEI
Короткий адрес: https://sciup.org/15018207
IDR: 15018207 | DOI: 10.5815/ijigsp.2021.06.03
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