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@article{195354,
        author = {Kallam Harshini and Kalluri Naga Poojitha and Gullapalli Lakshmi Sravanthi and Mr.K.SenthilKumararaja},
        title = {Face Recognition Based Attendance Management System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {7570-7575},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=195354},
        abstract = {Attendance management plays a vital role in educa-tional institutions and organizations. Traditional at-tendance methods such as manual registers and ID card systems are time-consuming and prone to human er-rors. To overcome these problems, a Face Recognition Based Attendance Management System is proposed. The system uses computer vision techniques to auto-matically identify and record attendance using facial recognition technology.The proposed system uses OpenCV and deep learning-based face recognition al-gorithms to detect and recognize faces in real time. The system captures facial images through a webcam and compares them with the stored dataset to identify stu-dents. Once the face is recognized, the attendance is automatically recorded in the database. This system improves efficiency, accuracy, and security compared to traditional methods. It eliminates proxy attendance and reduces manual work for teachers. The proposed solution is highly scalable and can be implemented in schools, colleges, and offices for automated attendance tracking.},
        keywords = {Face Recognition, Attendance System, OpenCV, Ma-chine Learning, Computer Vision.},
        month = {March},
        }