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@article{176652,
        author = {Sakshi Sathe and Vaishnavi Padlamwar},
        title = {Attendance Management System Using Face Recognition},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {7054-7058},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=176652},
        abstract = {Accurate attendance management is essential in educational and workplace settings. In both educational and professional contexts, accurate attendance management is crucial. Conventional approaches frequently have flaws and inefficiencies. This study introduces a Python Tkinter-based GUI-based facial recognition-based attendance system that uses OpenCV for real- time detection and recognition. The system’s goals are to improve usability, and accuracy. Initial findings show a user-friendly interface and good recognition accuracy. This study demonstrates how biometric technology can be used to track attendance effectively, providing a creative and useful way to expedite administrative procedures.},
        keywords = {Face Recognition, Attendance Management Sys- tem,OpenCV, Tkinter, Machine Learning, Real-Time Detection, Automated Attendance, LBPH, Haar Cascade, Computer Vision, Python, GUI, Efficiency, Educational Institutions.},
        month = {April},
        }