
The present project proposes an Automated Attendance Management System, based on Deep Learning- based Face Recognition technology to assist in modernizing and advancement of the once manual attendance keeping system in educational centers. The system relies on LBPH Face Recognizer that will detect the face and in real- time, thereby eliminating the necessity to conduct a manual roll call. Admin Module allows the administrator to utilize the information regarding the students, to train the face recognition model, to manage the attendance and to send the automated messages to the parents concerning the attendance and the school performance of the students. Student Module enables the student to demonstrate their presence using the assistance of facial recognition, check their profiles, and get their academic marks. The system also has added features of the ability to monitor the performance of the students in real time and effective communication with the parents via SMS notifications. Flask framework has been used to code the web interface thus making the site easy to use. This system improves the management side of the running of the educational institutions, improves efficient attendance of students to the learning institutions, and the students- parents communication.
Deep Learning, admin, student, parental engagement, LBPH face recognizer, flask, automated notification, SMS notification., real- time monitoring, Attendance Management, face recognition
Deep Learning, admin, student, parental engagement, LBPH face recognizer, flask, automated notification, SMS notification., real- time monitoring, Attendance Management, face recognition
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