Improving Lightweight Convolutional Neural Network for Facial Expression Recognition via Transfer Learning

Anggit Wikanningrum, Reza Fuad Rachmadi, Kohichi Ogata

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

10 Citations (Scopus)

Abstract

Image-based facial expression recognition is an important problem especially for analyzing the human emotion or feeling under a specific condition, such as while watching a movie scene or playing a computer game. Furthermore, the convolutional neural network (CNN) is one of the underlying technology proven to be applicable to image-based facial expression recognition problem. Unfortunately, the available CNN architecture that applied for image-based facial expression recognition problem only focuses on the accuracy instead of other factors, such as the number of parameters and the execution time. In this paper, we investigated whether transfer learning from a medium-size and large-size dataset is feasible to improve the performance of lightweight CNN architecture on image-based facial expression recognition problem. We use lightweight residual-based CNN architecture originally used for CIFAR dataset to analyze the effect of the transfer learning from five different datasets, including CIFAR10, CIFAR100, ImageNet32, CINC-10, and CASIA-WebFace. The FER+ (Facial Expression Recognition Plus) dataset is used to evaluate the lightweight CNN architecture performance. Experiments show that our lightweight CNN classifier can also be improved even when the transfer learning performing from middle-size dataset comparing when training the classifier from scratch.

Original languageEnglish
Title of host publication2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019 - Proceeding
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728129655
DOIs
Publication statusPublished - Nov 2019
Event2nd International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019 - Surabaya, Indonesia
Duration: 19 Nov 201920 Nov 2019

Publication series

Name2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019 - Proceeding
Volume2019-November

Conference

Conference2nd International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019
Country/TerritoryIndonesia
CitySurabaya
Period19/11/1920/11/19

Keywords

  • facial expression recognition
  • lightweight deep convolutional neural network
  • transfer learning

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