• Dr. Arun Kumar Marandi

Student involvement in academics is a significant issue in many educational institutions. Handling attendance papers manually in busy classes takes a long time. This article describes and evaluates an automatic student attendance system that may be utilized in closed classrooms that uses a PC to take photos of the classroom. Mobile automated classroom attendance management system based on facial recognition that does not need any additional equipment. The face recognition system was built using the Euclidean-based filtering technique and evaluated using three distinct face recognition algorithms. Teachers, students, and parents are all given three different mobile applications to use on their cell phones to track and execute the attendance process in real time. Several face identification algorithms based on learnt and handmade features are tested using a methodology that takes into consideration the number of pictures per person included in the gallery. Author utilized two deep learning techniques, Hear Cascading and Local Binary Trend Histogram (LBPH), with just one enrollment picture per participant reaching approximately 95% accuracy. We think that our face recognition-based automated student attendance system will save time for both instructors and students while also reducing false attendance.

Attendance, Monitoring System, Classroom Attendance, Face Recognition, Python.

"Attendance Management System Using Computer Vision", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 1, page no.409-414, January-2019, Available :http://www.jetir.org/papers/JETIRFT06078.pdf

"Attendance Management System Using Computer Vision", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 1, page no. pp409-414, January-2019, Available at : http://www.jetir.org/papers/JETIRFT06078.pdf