Investigating The Fusion of Classifiers Designed Under Different Bayes Errors

We investigate a number of parameters commonly affecting the design of a multiple classifier system in order to find when fusing is most beneficial. We extend our previous investigation to the case where unequal classifiers are combined. Results indicate that Sum is not affected by this parameter, h...

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Bibliographic Details
Main Authors: Fuad M. Alkoot, Josef Kittler
Format: Article
Language:English
Published: International Institute of Informatics and Cybernetics 2004-12-01
Series:Journal of Systemics, Cybernetics and Informatics
Subjects:
sum
Online Access:http://www.iiisci.org/Journal/CV$/sci/pdfs/P658547.pdf