International Journal of Computer Techniques Volume 12 Issue 3 | Real Time Attendance Marking System Integrates Webcam
Real-Time Attendance Marking System Integrates Webcam
International Journal of Computer Techniques – Volume 12 Issue 3, May – June 2025
Abstract
This study presents an innovative **AI-powered attendance marking system** integrating **YOLO object detection** for real-time **face recognition and attendance automation**. Traditional biometric methods can be **intrusive and inefficient**, whereas this system ensures **instantaneous identification, robust accuracy, and minimal manual intervention** using **deep learning techniques**.
Keywords
Real-time Attendance System, Facial Recognition, YOLO, Deep Learning, Automated Attendance, Image Processing, AI Attendance System.
Conclusion
The **YOLO-based real-time attendance system** significantly enhances **efficiency and automation** in tracking attendance. By leveraging deep learning, it **improves accuracy, reduces errors, and optimizes resource management**. Future research will explore **multi-modal biometric authentication and machine learning-driven attendance pattern analysis**.
References
- Kar, N. et al. (2012). “Study of implementing automated attendance system using face recognition technique.” Int. Journal of Computer and Communication Engineering.
- Kawaguchi, Y. et al. (2005). “Face recognition-based lecture attendance system.” The 3rd AEARU workshop on network education.
- Mekala, V. et al. (2019). “Face recognition-based attendance system.” Int. Journal of Innovative Technology and Exploring Engineering.
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