Multiple Face Recognition Attendance System

 Multiple Face Recognition Attendance System

1Kshitiz Gupta ,  2Abhinav Kumar Sharma , 3Gunjan  Agarwal
1 2Students , 3Assistant professor

* Information Technology Department , Raj Kumar Goel Institute Of  Technology

Abstract- When managed manually, keeping track of attendance can be quite time-consuming for teachers. This research study suggests a "Multiple Face Recognition Attendance System" that makes use of cutting-edge face recognition technologies for managing attendance in order to overcome this problem. The system achieves excellent accuracy and reliability by utilizing numerous face recognition methods, such as face detection, feature extraction, and matching. Face recognition technology is essential in today's digital world across many industries. By providing a more effective substitute for conventional techniques, it has revolutionized attendance management systems. The current manual attendance methods are time-consuming, difficult to maintain, and prone to proxy attendance. This system intends to develop a class attendance system that makes use of facial recognition. Modern deep learning algorithms are used by the Multiple Face Recognition Attendance System (MFRAS) to instantly identify faces in live video streams that have been collected by surveillance cameras. By leveraging a database of enrolled individuals' facial features, the system accurately identifies and verifies each person's identity. The MFRAS offers significant improvements over traditional attendance systems, enhancing accuracy and reducing processing time. In conclusion, the Multiple Face Recognition Attendance System (MFRAS) provides a reliable, secure, and efficient solution for attendance management in educational institutions.

Keywords-  Attendance Management ,  Biometric Identification , Face detection , Face Recognition System ,Real Time Face Recognition .