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- W3083117568 abstract "Facial recognition has always been a field of continuous development and research due to its usage in different areas such as security and robotics. It has gained even more popularity and interest by the researchers with the recent advancements in artificial intelligence and deep learning, which improved the robustness of facial recognition systems. In this paper, we focus on facial recognition using deep learning on small data sets with a limited number of individuals, for that we propose a local features based facial recognition approach that combines the robustness of feature extraction of CNN with the Harris corner detector. The experimental results of our proposed method surpassed the results of classical methods (LBP, Eigen Face, and Fisher Face) as well as recent works on Georgia Tech Face Database and AR Face Database and proved its efficiency and its robustness in different conditions including illumination variation, face pose variation, changes in facial expressions and face occlusions." @default.
- W3083117568 created "2020-09-11" @default.
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- W3083117568 date "2020-09-06" @default.
- W3083117568 modified "2023-09-30" @default.
- W3083117568 title "Face Recognition Based on Harris Detector and Convolutional Neural Networks" @default.
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- W3083117568 doi "https://doi.org/10.1007/978-3-030-58861-8_12" @default.
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