A Hybrid Approach with the Wavelet Transform, Modular Neural Networks and Fuzzy Integrals for Face and Fingerprint Recognition

被引：0
|
作者：
Alvarado, Manuel [1 ]
Melin, Patricia [2 ]
Lopez, Miguel [2 ]
Mancilla, Alejandra [2 ]
Castillo, Oscar [2 ]
机构：
[1] Tijuana Inst Technol, Tijuana, Mexico
[2] Inst Technol, Grad Div Tijuana, Tijuana, Mexico
来源：
HIMA: 2009 IEEE WORKSHOP ON HYBRID INTELLIGENT MODELS AND APPLICATIONS | 2009年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper a new approach for pattern recognition using wavelets, modular neural networks and fuzzy logic is presented. A new architecture for modular neural networks for achieving pattern recognition in the particular case of human faces and fingerprints is described. Also, the method for achieving response integration is based on the fuzzy Sugeno integral with some modifications for the particular application. Response integration is required to combine the outputs of all the modules in the modular network. The Wavelet Transform is used for image compression.
引用
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页码：19 / +
页数：2
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