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@article{151978,
        author = {Akshay Shukla and Piyush Kumar Singh and Alankar Mishra and Akshaya Mishra and Abhyanshu Yadav},
        title = {Face Recognition Multi-Management System},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {2},
        pages = {94-98},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=151978},
        abstract = {Face recognition systems play a critical role in practically every area in today's digital economy. One of the most widely utilized biometrics is face recognition. It can be used for security, authentication, and identity, among other things. Despite having lower accuracy than iris and fingerprint recognition, it is commonly utilized due to its contactless and non-invasive nature. Face recognition systems can also be used to track attendance in places like schools, colleges, and companies. Because the existing manual attendance system is time consuming and difficult to maintain, this system intends to create a class attendance system that employs the concept of face recognition. And there may be prospects of proxy attendance. As a result, the demand for this system grows. Database development, face detection, face recognition, and attendance updating are the four steps of this system. The photos of the kids in class are used to generate the database. The Haar-Cascade classifier and the Local Binary Pattern Histogram technique are used to detect and recognize faces, respectively. Faces are discovered and recognized from the classroom's live streaming footage},
        keywords = {},
        month = {},
        }