Imperfect Pattern Recognition Using The Fuzzy Measure Theory

IDEAL'09: Proceedings of the 10th international conference on Intelligent data engineering and automated learning(2009)

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摘要
This paper aims to provide a unified framework to deal with information imperfection and heterogeneity using possibility theory. in addition to information conflict and scarcity using Dempster-Shafer theory in order to classify imperfectly-described medical images. The proposed method is very robust and general. It can be applied without modification to any other database.
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关键词
pattern recognition,possibility theory,Dempster-Shafer theory,similarity measuring
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