Neural network structures for expression recognition

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

Neural network structures for expression recognition

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

INF - Computer and Mathematical Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

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 language	English
Title of host publication	Proceedings of the International Joint Conference on Neural Networks
Editors	Anon
Publisher	Publ by IEEE
Pages	1431-1432
Number of pages	2
ISBN (Print)	0780314212
Publication status	Published - 1993 Dec 1
Event	Proceedings of 1993 International Joint Conference on Neural Networks. Part 2 (of 3) - Nagoya, Jpn Duration: 1993 Oct 25 → 1993 Oct 29

Publication series

Name	Proceedings of the International Joint Conference on Neural Networks
Volume	2

Other

Other	Proceedings of 1993 International Joint Conference on Neural Networks. Part 2 (of 3)
City	Nagoya, Jpn
Period	93/10/25 → 93/10/29

ASJC Scopus subject areas

Software
Artificial Intelligence

Cite this

Neural network structures for expression recognition. / Ding, J.; Shimamura, M.; Kobayashi, H. et al.

Proceedings of the International Joint Conference on Neural Networks. ed. / Anon. Publ by IEEE, 1993. p. 1431-1432 (Proceedings of the International Joint Conference on Neural Networks; Vol. 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Ding, J, Shimamura, M, Kobayashi, H & Nakamura, T 1993, Neural network structures for expression recognition. in Anon (ed.), Proceedings of the International Joint Conference on Neural Networks. Proceedings of the International Joint Conference on Neural Networks, vol. 2, Publ by IEEE, pp. 1431-1432, Proceedings of 1993 International Joint Conference on Neural Networks. Part 2 (of 3), Nagoya, Jpn, 93/10/25.

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title = "Neural network structures for expression recognition",

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.",

author = "J. Ding and M. Shimamura and H. Kobayashi and T. Nakamura",

year = "1993",

month = dec,

day = "1",

language = "English",

isbn = "0780314212",

series = "Proceedings of the International Joint Conference on Neural Networks",

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pages = "1431--1432",

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note = "Proceedings of 1993 International Joint Conference on Neural Networks. Part 2 (of 3) ; Conference date: 25-10-1993 Through 29-10-1993",

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TY - GEN

T1 - Neural network structures for expression recognition

AU - Ding, J.

AU - Shimamura, M.

AU - Kobayashi, H.

AU - Nakamura, T.

PY - 1993/12/1

Y1 - 1993/12/1

N2 - 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.

AB - 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.

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UR - http://www.scopus.com/inward/citedby.url?scp=0027867615&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:0027867615

SN - 0780314212

T3 - Proceedings of the International Joint Conference on Neural Networks

SP - 1431

EP - 1432

BT - Proceedings of the International Joint Conference on Neural Networks

A2 - Anon, null

PB - Publ by IEEE

T2 - Proceedings of 1993 International Joint Conference on Neural Networks. Part 2 (of 3)

Y2 - 25 October 1993 through 29 October 1993

ER -

Neural network structures for expression recognition

Abstract

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ASJC Scopus subject areas

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