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@article{176172,
        author = {Jeevabarathi P and Karthik S and Kamal D and Vaishnavi K},
        title = {Real-Time Face Authentication for Attendance Management with Anti-Spoofing Integration},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {5912-5917},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=176172},
        abstract = {The increasing demand for automated attendance systems in the school and corporate industries led to the development of a Real-Time Smart Attendance System based on facial recognition and anti-spoofing. Fingerprint scanners and roll calls are unsanitary, time-consuming, and prone to errors. Our system is utilizing BlazeFace to recognize faces in real-time, FaceNet to make accurate recognition, and an anti-spoofing CNN-based system to cancel out fake check-ins. The solution offers a contactless, real-time, and scalable answer with low intervention that ensures safe tracking of attendance. There is a cloud central database that enables administrators to monitor attendance easily.},
        keywords = {Face Recognition, Anti-Spoofing, BlazeFace, FaceNet, Convolutional Neural Network (CNN), Attendance System.},
        month = {April},
        }