Workpiece recognition by the combination of multiple simplified fuzzy ARTMAP

Authors:
Zhanhui Yuan;Gang Wang;Jihua Yang
Affiliations:
Mechanical Engineering School, Tianjin University, NanKai Division, Tianjin City, P.R. China;Mechanical Engineering School, Tianjin University, NanKai Division, Tianjin City, P.R. China;Mechanical Engineering School, Tianjin University, NanKai Division, Tianjin City, P.R. China
Venue:
ICONIP'06 Proceedings of the 13th international conference on Neural information processing - Volume Part III
Year:
2006

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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.