Abstract
Face recognition is a biometric system used to identify a person from digital images; its application is primarily for security and monitoring purposes. Recently, there have been more research works on deep neural network for facial recognition achieving positive results. In this study, we propose an effective model to solve face recognition problem which could be applied to identify directly from camera. In particular, the study focuses on two phases: face detection and face identification. The face detection method that we propose uses HOG features and SVM linear classifier. The face recognition model is proposed based on CNN—convolution neural network. The efficiency of the model is evaluated on the FEI, LFW, UOF datasets, and the results show that the proposed model achieves high accuracy.
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Hung, B.T. (2021). Face Recognition Using Hybrid HOG-CNN Approach. In: Kumar, R., Quang, N.H., Kumar Solanki, V., Cardona, M., Pattnaik, P.K. (eds) Research in Intelligent and Computing in Engineering. Advances in Intelligent Systems and Computing, vol 1254. Springer, Singapore. https://doi.org/10.1007/978-981-15-7527-3_67
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DOI: https://doi.org/10.1007/978-981-15-7527-3_67
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