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ASME Press Select Proceedings
Intelligent Engineering Systems Through Artificial Neural Networks, Volume 17
Editor
ISBN-10:
0791802655
No. of Pages:
650
Publisher:
ASME Press
Publication date:
2007
eBook Chapter
68 Interval Type-2 Fuzzy Logic for Improving Feature Extraction and Response Integration in Modular Neural Networks for Image Recognition
By
Oscar Castillo
Oscar Castillo
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Page Count:
6
-
Published:2007
Citation
Mendoza, O, Melin, P, & Castillo, O. "Interval Type-2 Fuzzy Logic for Improving Feature Extraction and Response Integration in Modular Neural Networks for Image Recognition." Intelligent Engineering Systems Through Artificial Neural Networks, Volume 17. Ed. Dagli, CH. ASME Press, 2007.
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The combination of Soft Computing techniques allows the improvement of intelligent systems with different hybrid approaches. In this work we consider two parts of a Modular Neural Network for image recognition, where a Type-2 Fuzzy Inference System (FIS 2) makes a great difference. The first FIS 2 is used for feature extraction in training data, and the second one to find the ideal parameters for the integration method of the modular neural network.
Abstract
Introduction
Type-2 Fuzzy Logic for Edge Detection
Experimental Results
Conclusions
References
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