Revolutionizing Attendance Tracking with Artificial Intelligence (AI) Technologies

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The AI attendance system automates tracking, reducing human error effectively while addressing proxy attendance issues.
Utilizing facial recognition, the system employs the Haar Cascade Classifier and LPBH for accurate performance under indoor lighting conditions.
Built with OpenCV and Python, the solution features a graphical interface for user access and administrative tasks like attendance logging.
The modular architecture allows for expansion in classrooms and training centers, providing a modern alternative to traditional attendance methods.

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This analysis demonstrates a face recognition system for attendance tracking in educational settings, suggesting improvements over outdated methods.

Anand et al. (2025) studied this question.

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This analysis demonstrates a face recognition system for attendance tracking in educational settings, suggesting improvements over outdated methods.