• ABHISHEK SINGH RAWAT
• AKASH YADAV
• GOPAL TIBREWAL
• SAYUJ KOUL
• PRIYANKA PAYGUDE

Attendance is essential part of education assessment system. Almost all schools and universities use conventional attendance sheet for attendance management which is laborious, time consuming and less efficient. Few of Universities have moved onto finger based biometrics for attendance monitoring but still it is not widely used due to expenses and setup system which requires hardware and software installation on the other hand facial recognition based attendance monitoring can be done with a camera and software no additional hardware is required. Moreover the cheap cost of camera and wide availability also makes attendance based on facial recognition more suitable and easily applicable. The performance and accurate nature of attendance management based on image recognition makes it more promising and reliable for such application. We selected model based on deep neural network which was found to have better performance than other algorithms like support vector machine and classifier cascades.

Attendance, biometrics, face detection, face recognition, eye blinking, MTCNN, Inception- resnet

"Automatic Attendance Monitoring", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.542-546, June-2019, Available :http://www.jetir.org/papers/JETIR1906367.pdf

"Automatic Attendance Monitoring", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp542-546, June-2019, Available at : http://www.jetir.org/papers/JETIR1906367.pdf