Age and Gender Prediction from Face Images Using Convolutional Neural Network

Koichi Ito, Hiroya Kawai, Takehisa Okano, Takafumi Aoki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publication2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages7-11
Number of pages5
ISBN (Electronic)9789881476852
DOIs
Publication statusPublished - 2019 Mar 4
Event10th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Honolulu, United States
Duration: 2018 Nov 122018 Nov 15

Publication series

Name2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings

Conference

Conference10th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018
CountryUnited States
CityHonolulu
Period18/11/1218/11/15

ASJC Scopus subject areas

  • Information Systems

Fingerprint Dive into the research topics of 'Age and Gender Prediction from Face Images Using Convolutional Neural Network'. Together they form a unique fingerprint.

Cite this