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Original Article

Smart Face Recognition System for Secure Authentication, Real-Time Monitoring, and Automated Alerting

Radha G1 Neil A2 Hari prasath M3 Sri varshini B4 Antwi Michael5
1 Assistant Professor, Department of CSE, Rathinam Technical Campus Coimbatore, Tamil Nadu, India. 2 3 4 5 Final Year Students, Department of CSE, Rathinam Technical Campus Coimbatore, Tamil Nadu, India.

Published Online: November-December 2025

Pages: 17-20

References

1. Taigman, Y., et al. “DeepFace: Closing the Gap to Human-Level Performance in Face Verification.” IEEE CVPR, 2014.
2. Schroff, F., et al. “FaceNet: A Unified Embedding for Face Recognition.” Google Research, 2015.
3. Parkhi, O. M., et al. “Deep Face Recognition.” BMVC, 2015.
4. Zhang, K., et al. “Joint Face Detection and Alignment Using Multi-Task Cascaded CNN.” IEEE SPL, 2016.
5. OpenCV Documentation. “Real-Time Computer Vision.” 2023.
6. Deng, J., et al. “ArcFace: Additive Angular Margin Loss for Deep Face Recognition.” CVPR, 2019.
7. Khan, A., “Biometric Authentication Systems.” IEEE Access, 2021.
8. Goodfellow, I., et al. “Deep Learning.” MIT Press, 2016.
9. Kumar, R., “Security Enhancement Through Face Recognition Systems.” Journal of Information Security, 2022.
10. OpenFace Project. “Open-Source Face Recognition Tools.” 2023.

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