Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/43023
Title: Face recognition based on linear classifiers combination
Authors: Jing, X
Zhang, D 
Keywords: Face recognition
Linear classifiers combination
Maximum complementariness criterion
Genetic algorithm
Fisherface feature
Issue Date: 2003
Publisher: Elsevier
Source: Neurocomputing, 2003, v. 50, p. 485-488 How to cite?
Journal: Neurocomputing 
Abstract: In this paper, an approach that uses a combination of linear classifiers is applied to face recognition. We propose a novel criterion for the combination, the maximum complementariness criterion, which is used to construct the fitness function for a genetic algorithm (GA). A GA is then used to generate the rational weights for the classifiers. Experiments show that our approach can successfully improve the performance of the classification for face recognition using the commonly used Fisherface features.
URI: http://hdl.handle.net/10397/43023
ISSN: 0925-2312
EISSN: 1872-8286
DOI: 10.1016/S0925-2312(02)00674-4
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