Multiple facial recognition and automated attendance posting: A modern approach

This paper presents an advanced system for automated attendance using multi-face recognition technology. The system captures real-time video streams, processes frames to match faces against a secure database, and allows new student registration when unmatched. A teacher-only login prevents unauthorized access, ensuring data integrity. The model efficiently recognizes multiple students simultaneously, making it ideal for large classroom setups. It also sends real-time email notifications to students and parents and uses advanced analytics to detect attendance irregularities. Powered by deep learning, the system delivers high accuracy under varied lighting conditions, enhancing precision, efficiency, and data security in educational institutions.