TY - GEN
T1 - A survey of deep face recognition in the wild
AU - Prihasto, Bima
AU - Choirunnisa, Shabrina
AU - Nurdiansyah, Muhammad Ishak
AU - Mathulaprangsan, Seksan
AU - Chu, Vivian Ching Mei
AU - Chen, Shi Huang
AU - Wang, Jia Ching
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/7/2
Y1 - 2016/7/2
N2 - Face recognition is one of the significant topics in the biometric security system. This topic has been progressively developed by deep learning approaches, one of the most favorite techniques in recent years. In this paper, we propose a survey of existing works on face recognition using deep learning algorithms. All of the surveyed methods were compared on the labeled face in the wild (LFW) database.
AB - Face recognition is one of the significant topics in the biometric security system. This topic has been progressively developed by deep learning approaches, one of the most favorite techniques in recent years. In this paper, we propose a survey of existing works on face recognition using deep learning algorithms. All of the surveyed methods were compared on the labeled face in the wild (LFW) database.
KW - Deep learning
KW - Face recognition
KW - LFW dataset
UR - http://www.scopus.com/inward/record.url?scp=85049186204&partnerID=8YFLogxK
U2 - 10.1109/ICOT.2016.8278983
DO - 10.1109/ICOT.2016.8278983
M3 - 會議論文篇章
AN - SCOPUS:85049186204
T3 - 2016 International Conference on Orange Technologies, ICOT 2016
SP - 76
EP - 79
BT - 2016 International Conference on Orange Technologies, ICOT 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 International Conference on Orange Technologies, ICOT 2016
Y2 - 18 December 2016 through 20 December 2016
ER -