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Workpiece Recognition by the Combination of Multiple Simplified Fuzzy ARTMAP.

Authors :
King, Irwin
Jun Wang
Laiwan Chan
DeLiang Wang
Zhanhui Yuan
Gang Wang
Jihua Yang
Source :
Neural Information Processing (9783540464846); 2006, p1063-1069, 7p
Publication Year :
2006

Abstract

Simplified fuzzy ARTMAP(SFAM) is a simplification of fuzzy ARTMAP(FAM) in reducing architectural redundancy and computational overhead. The performance of individual SFAM depends on the ordering of training sample presentation. A multiple classifier combination scheme is proposed in order to overcome the problem. The sum rule voting algorithm combines the results from several SFAM's and generates reliable and accurate recognition conclusion. A confidence vector is assigned to each SFAM. The confidence element value can be dynamically adjusted according to the historical achievements. Experiments of recognizing mechanical workpieces have been conducted to verify the proposed method. The experimental results have shown that the fusion approach can achieve reliable recognition. Keywords: ARTMAP, Neural network, workpiece recognition. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540464846
Database :
Complementary Index
Journal :
Neural Information Processing (9783540464846)
Publication Type :
Book
Accession number :
32964070
Full Text :
https://doi.org/10.1007/11893295_117