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2D Principal Component Analysis for Face and Facial-Expression Recognition

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4 Author(s)

Although it shows enormous potential as a feature extractor, 2D principal component analysis produces numerous coefficients. Using a feature-selection algorithm based on a multiobjective genetic algorithm to analyze and discard irrelevant coefficients offers a solution that considerably reduces the number of coefficients, while also improving recognition rates.

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Computing in Science & Engineering  (Volume:13 ,  Issue: 3 )
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