Many theoretical and experimental studies have shown that a multiple classi? er system is an e? ective technique for reducing prediction errors [9, 10, 11, 20, 19]. These studies …
The theory and practice of Multiple Classifier Systems (MCS) and related methods address the issues surrounding the optimality of decision-making in a multiple classifier framework …
V Gunes, M Ménard, S Petitrenaud - Handbook of Pattern …, 2010 - World Scientific
As multiple experts can confront and exchange their ideas in order to improve the decision- making process, a pattern recognition system can use several classifiers in order to improve …
More than a decade ago, combining multiple classifiers was proposed as a possible solution to the problems posed by the traditional pattern classification approach which involved …
The belief that a committee of people make better decisions than any individual is widely held and appreciated. We also understand that, for this to be true, the members of the …
D Partridge, N Griffith - Pattern Analysis & Applications, 2002 - Springer
One vigorous branch of research aimed at improving the performance of pattern recognition systems explores the possibilities for exploiting the differences between a set of variously …
J Kittler, F Roli - Lecture notes in computer science, 2000 - Springer
These proceedings are a record of the Multiple Classifier Systems Workshop, MCS 2009, held at the University of Iceland, Reykjavik, Iceland in June 2009. Being the eighth in a well …
PR Cavalin, R Sabourin, CY Suen - Neural computing and applications, 2013 - Springer
In this paper we propose a new approach for dynamic selection of ensembles of classifiers. Based on the concept named multistage organizations, the main objective of which is to …
L Lam - International workshop on multiple classifier systems, 2000 - Springer
Much work has been done in the past decade to combine decisions of multiple classifiers in order to obtain improved recognition results. Many methodologies have been designed and …