Abstract: Face recognition technology has become an effective and automated solution for managing attendance in academic and organizational settings. With advancements in machine learning and computer vision, it is now possible to recognize individuals accurately in real time using facial features. This project presents a Face Recognition Attendance Management System that automates the attendance process by detecting and verifying faces through live camera input. The system uses techniques such as face detection, feature extraction, and classification, with the help of Convolutional Neural Networks (CNN). We analyze the system’s performance under varying conditions such as lighting and face angles, and evaluate its accuracy and reliability. Our study demonstrates that integrating face recognition with attendance systems enhances security, saves time, and minimizes the chances of proxy attendance.
Keywords: Face Recognition, Attendance Management, Machine Learning, Deep Learning, Computer Vision, Convolutional Neural Networks (CNN), Image Processing.
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DOI:
10.17148/IJARCCE.2025.145106
