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Face recognition using modular neural networks and the fuzzy Sugeno integral for response integration
Author(s) -
Melin Patricia,
Felix Cristina,
Castillo Oscar
Publication year - 2005
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.20066
Subject(s) - modular design , computer science , artificial neural network , fuzzy logic , face (sociological concept) , artificial intelligence , facial recognition system , modular neural network , neuro fuzzy , pattern recognition (psychology) , machine learning , time delay neural network , fuzzy control system , programming language , social science , sociology
We describe a new approach for face recognition using modular neural networks with a fuzzy logic method for response integration. We proposed a new architecture for modular neural networks for achieving pattern recognition in the particular case of human faces. Also, the method for achieving response integration is based on the fuzzy Sugeno integral. Response integration is required to combine the outputs of all the modules in the modular network. We have applied the new approach for face recognition to a real database of faces of students at our institution. Recognition rates with the modular approach were compared against the monolithic single neural network approach to measure the improvement. The results of the new modular neural network approach were excellent overall and also in comparison to the monolithic approach. © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 275–291, 2005.