An integrated fuzzy cells-classifier

descriptionPublicationkeyboard_double_arrow_right Article , Part of book or chapter of book , Conference object 01 Jan 2006 Italy English Publisher:Elsevier BVJournal:Image and Vision Computing, volume 25, pages 214-219 (issn: 0262-8856,

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Authors: LO BOSCO, Giosue';

doi: 10.1016/j.imavis.2006.01.031 , 10.1007/10983652_32

handle: 10447/47512 , 10447/21485

An integrated fuzzy cells-classifier

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Abstract

This paper introduces a genetic algorithm able to combine different classifiers based on different distance functions. The use of a genetic algorithm is motivated by the fact that the combination phase is based on the optimization of a vote strategy. The method has been applied to the classification of four types of biological cells, results show an improvement of the recognition rate using the genetic algorithm combination strategy compared with the recognition rate of each single classifier.

Country

Italy

Related Organizations

University of Palermo
Italy
University of Palermo
Argentina

Keywords

Evolutionary algorithms, Classifier ensemble, Classifier fusion; Clustering; Fuzzy sets; Genetic algorithms; Multiple classifiers

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