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