TY - GEN
T1 - Facial Age Estimation by Curriculum Learning
AU - Wang, Wei
AU - Ishikawa, Takaaki
AU - Watanabe, Hiroshi
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/10/13
Y1 - 2020/10/13
N2 - Curriculum learning has been widely used in training neural networks because of its significant improvements in generalization capability. However, it has not been applied to age estimation tasks. In this paper, we incorporate curriculum learning into age estimation. Experimental result of the proposed method on AFAD database for age prediction shows a substantial reduction of the prediction error compared to the traditional training strategy.
AB - Curriculum learning has been widely used in training neural networks because of its significant improvements in generalization capability. However, it has not been applied to age estimation tasks. In this paper, we incorporate curriculum learning into age estimation. Experimental result of the proposed method on AFAD database for age prediction shows a substantial reduction of the prediction error compared to the traditional training strategy.
KW - age estimation
KW - convolutional neural network
KW - curriculum learning
KW - feature extraction
UR - http://www.scopus.com/inward/record.url?scp=85099361821&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85099361821&partnerID=8YFLogxK
U2 - 10.1109/GCCE50665.2020.9291929
DO - 10.1109/GCCE50665.2020.9291929
M3 - Conference contribution
AN - SCOPUS:85099361821
T3 - 2020 IEEE 9th Global Conference on Consumer Electronics, GCCE 2020
SP - 138
EP - 139
BT - 2020 IEEE 9th Global Conference on Consumer Electronics, GCCE 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th IEEE Global Conference on Consumer Electronics, GCCE 2020
Y2 - 13 October 2020 through 16 October 2020
ER -