TY - GEN
T1 - Age and Gender Prediction from Face Images Using Convolutional Neural Network
AU - Ito, Koichi
AU - Kawai, Hiroya
AU - Okano, Takehisa
AU - Aoki, Takafumi
N1 - Publisher Copyright:
© 2018 APSIPA organization.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - Attribute information such as age and gender improves the performance of face recognition. This paper proposes an age and gender prediction method from face images using convolutional neural network. Through a set of experiments using public face databases, we demonstrate that the proposed method exhibits the efficient performance on age and gender prediction compared with conventional methods.
AB - Attribute information such as age and gender improves the performance of face recognition. This paper proposes an age and gender prediction method from face images using convolutional neural network. Through a set of experiments using public face databases, we demonstrate that the proposed method exhibits the efficient performance on age and gender prediction compared with conventional methods.
UR - http://www.scopus.com/inward/record.url?scp=85063536152&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85063536152&partnerID=8YFLogxK
U2 - 10.23919/APSIPA.2018.8659655
DO - 10.23919/APSIPA.2018.8659655
M3 - Conference contribution
AN - SCOPUS:85063536152
T3 - 2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings
SP - 7
EP - 11
BT - 2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018
Y2 - 12 November 2018 through 15 November 2018
ER -