Abstract
In this paper, we consider two multi-face recognition systems using deep and machine learning algorithms. Specifically, one is based on the Haar cascade algorithm coupled with the Local Binary Patterns (LBP) classification approach and the other one on the Histogram of Orianted Gradients (HOG) descriptors coupled with the Convolutional Neural Network (CNN) algorithm. We also carry out an exhaustive comparison between the two systems. The simulation results show clearly that both systems have high face detection rates. However, the deep learning-based system outperforms the machine learning-Based system in the face recognition task.
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Alane, B., Saad, B. (2022). Multi-face Recognition Systems Based on Deep and Machine Learning Algorithms. In: Ragab Hassen, H., Batatia, H. (eds) Proceedings of the International Conference on Applied CyberSecurity (ACS) 2021. ACS 2021. Lecture Notes in Networks and Systems, vol 378. Springer, Cham. https://doi.org/10.1007/978-3-030-95918-0_10
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DOI: https://doi.org/10.1007/978-3-030-95918-0_10
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