A Comparative Analysis of Various Methods for Attendance Framework Based on Real-Time Face Recognition Technology
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-7615-5_40
Reference16 articles.
1. Yang H, Han X (2020) Face recognition attendance system based on real-time video processing. IEEE Access 8:159143–159150. https://doi.org/10.1109/ACCESS.2020.3007205
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3. Abuzneid MA, Mahmood A (2018) Enhanced human face recognition using LBPH descriptor, multi-KNN, and back-propagation neural network. IEEE Access 6:20641–20651. https://doi.org/10.1109/ACCESS.2018.2825310
4. Awais M et al (2019) Real-time surveillance through face recognition using HOG and feedforward neural networks. IEEE Access 7:121236–121244. https://doi.org/10.1109/ACCESS.2019.2937810
5. Zhao H, Liang XJ, Yang P (2013) Research on face recognition based on embedded system. Math Prob Eng 2013(6) Article ID 519074. https://doi.org/10.1155/2013/519074
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