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- W2994725695 abstract "<p><span>In the last decade, facial recognition techniques are considered the most important fields of research in biometric technology. In this research paper, we present a Face Recognition (FR) system divided into three steps: The Viola-Jones face detection algorithm, facial image enhancement using Modified Contrast Limited Adaptive Histogram Equalization algorithm (M-CLAHE), and feature learning for classification. For learning the features followed by classification we used VGG16, ResNet50 and Inception-v3 Convolutional Neural Networks (CNN) architectures for the proposed system. Our experimental work was performed on the Extended Yale B database and CMU PIE face database. Finally, the comparison with the other methods on both databases shows the robustness and effectiveness of the proposed approach. Where the Inception-v3 architecture has achieved a rate of 99, 44% and 99, 89% respectively.</span></p>" @default.
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- W2994725695 date "2020-05-01" @default.
- W2994725695 modified "2023-10-18" @default.
- W2994725695 title "Illumination-robust face recognition based on deep convolutional neural networks architectures" @default.
- W2994725695 doi "https://doi.org/10.11591/ijeecs.v18.i2.pp1015-1027" @default.
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