Neural network structures for expression recognition

J. Ding, M. Shimamura, H. Kobayashi, T. Nakamura

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

Abstract

The topic of expression recognition using back-propagation neural networks has been proposed before[1]. In this paper, we build up expression features models and then apply them to the network structures for expression recognition, focusing on how to determine the number of hidden nodes and initialize the weights. Moreover, the simulation results of our methods are provided to show the ability of the back-propagation neural networks for recognizing facial expressions.

Original languageEnglish
Title of host publicationProceedings of the International Joint Conference on Neural Networks
Editors Anon
PublisherPubl by IEEE
Pages1431-1432
Number of pages2
ISBN (Print)0780314212
Publication statusPublished - 1993 Dec 1
EventProceedings of 1993 International Joint Conference on Neural Networks. Part 2 (of 3) - Nagoya, Jpn
Duration: 1993 Oct 251993 Oct 29

Publication series

NameProceedings of the International Joint Conference on Neural Networks
Volume2

Other

OtherProceedings of 1993 International Joint Conference on Neural Networks. Part 2 (of 3)
CityNagoya, Jpn
Period93/10/2593/10/29

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

Fingerprint Dive into the research topics of 'Neural network structures for expression recognition'. Together they form a unique fingerprint.

Cite this