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Hybrid GAs for Eigen-based facial recognition

机译:用于基于特征的面部识别的混合气体

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摘要

In this paper, we have performed an evaluation of genetic-based feature selection and weighting on the PCA-based face recognition. This work highlights the first attempt of applying Genetic Algorithm (GA) based feature selection on the Eigenface method. The results show that genetic-based feature selection reduces the number of features needed by approximately 50% while improving the identification accuracy over the baseline. Genetic-based feature weighting significantly improves the accuracy from an 87.14% to a 92.5% correct recognition rate.
机译:在本文中,我们已经对基于PCA的面部识别进行了基于遗传的特征选择和加权的评估。 这项工作突出显示在突脸方法上应用基于遗传算法(GA)特征选择的第一次尝试。 结果表明,基于遗传的特征选择减少了大约50%所需的特征数,同时提高基线上的识别精度。 基于遗传的特征权重显着提高了87.14%的准确性,达到了92.5%的正确识别率。

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