Transfer Learning for Gender and Age Prediction

Cao Hong Nga, Khai Thinh Nguyen, Nghi C. Tran, Jia Ching Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this work, we propose a transfer learning pipeline for gender and age prediction using images from IMDB-WIKI dataset. Firstly, we freeze all layers in pre-trained ImageNet models. Then, the models are trained for four stages with scheduled learning rates and the blocks of layers are unlocked consecutively in accordance to the schedule. We apply multi-output neural network paradigm to predict age and gender simultaneously and the final loss function is based on the combination of age and gender losses. In our approach, the model has better performance than that of the non-pre-trained model because the later stages of our models reuse features extracted from the pre-trained early stages.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728173993
DOIs
StatePublished - 28 Sep 2020
Event7th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020 - Taoyuan, Taiwan
Duration: 28 Sep 202030 Sep 2020

Publication series

Name2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020

Conference

Conference7th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020
Country/TerritoryTaiwan
CityTaoyuan
Period28/09/2030/09/20

Keywords

  • age and gender prediction
  • convolutional neural network
  • neural networks
  • transfer learning

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