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» A Method for Error Rejection in Multiple Classifier Systems
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ESWA
2006
165views more  ESWA 2006»
13 years 7 months ago
Optimal ensemble construction via meta-evolutionary ensembles
In this paper we propose a meta-evolutionary approach to improve on the performance of individual classifiers. In the proposed system, individual classifiers evolve, competing to ...
YongSeog Kim, W. Nick Street, Filippo Menczer
ICPR
2008
IEEE
14 years 2 months ago
Adaptive asymmetrical SVM and genetic algorithms based iris recognition
We propose Genetic Algorithms to improve the feature subset selection by combining the valuable outcomes from multiple feature selection methods. This paper also motivates the use...
Kaushik Roy 0002, Prabir Bhattacharya
IJCNN
2007
IEEE
14 years 2 months ago
Distance-based Disagreement Classifiers Combination
— We present a methodology to analyze Multiple Classifiers Systems (MCS) performance, using the diversity concept. The goal is to define an alternative approach to the convention...
Cinthia Obladen de Almendra Freitas, João M...
SMC
2007
IEEE
156views Control Systems» more  SMC 2007»
14 years 2 months ago
Dynamic fusion of classifiers for fault diagnosis
—This paper considers the problem of temporally fusing classifier outputs to improve the overall diagnostic classification accuracy in safety-critical systems. Here, we discuss d...
Satnam Singh, Kihoon Choi, Anuradha Kodali, Krishn...
VTC
2008
IEEE
110views Communications» more  VTC 2008»
14 years 2 months ago
Performance Analysis on Maximum Likelihood Detection for Two Input Multiple Output Systems
-This paper addresses the problem of performance analysis for maximum likelihood (ML) detection in two-input multiple-output multiplexing systems. A novel analytical method is pres...
Wei Peng, Shaodan Ma, Tung-Sang Ng, Jiangzhou Wang...