Facial Age Estimation by Curriculum Learning

Wei Wang, Takaaki Ishikawa, Hiroshi Watanabe

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

Abstract

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.

Original languageEnglish
Title of host publication2020 IEEE 9th Global Conference on Consumer Electronics, GCCE 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages138-139
Number of pages2
ISBN (Electronic)9781728198026
DOIs
Publication statusPublished - 2020 Oct 13
Event9th IEEE Global Conference on Consumer Electronics, GCCE 2020 - Kobe, Japan
Duration: 2020 Oct 132020 Oct 16

Publication series

Name2020 IEEE 9th Global Conference on Consumer Electronics, GCCE 2020

Conference

Conference9th IEEE Global Conference on Consumer Electronics, GCCE 2020
CountryJapan
CityKobe
Period20/10/1320/10/16

Keywords

  • age estimation
  • convolutional neural network
  • curriculum learning
  • feature extraction

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering
  • Media Technology
  • Instrumentation
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition

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