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Automatic Attendance Management System under Unconstrained Video using Face Recognition
Meiappane. A1, Giridharan. S2, Jayaram. V3, Manikandan. K4, Vishnu. M5

1Dr. A. Meiappane, Associate Professor, Department of Information Technology, Manakula Vinayagar Institute of Technology, Puducherry, India.
2S. Giridharan, Final Year, Department of Information Technology, Manakula Vinayagar Institute of Technology, Puducherry, India.
3V. Jayaram, Final Year, Department of Information Technology, Manakula Vinayagar Institute of Technology, Puducherry, India.
4K. Manikandan, Final Year, Department of Information Technology, Manakula Vinayagar Institute of Technology, Puducherry, India.
5M. Vishnu, Final Year, Department of Information Technology Manakula Vinayagar Institute of Technology, Puducherry, India.
Manuscript received on July 16, 2020. | Revised Manuscript received on July 29, 2020. | Manuscript published on August 10, 2020. | PP: 229-232 | Volume-9 Issue-10, August 2020 | Retrieval Number: 100.1/ijitee.J74600891020 | DOI: 10.35940/ijitee.J7460.0891020
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Attendance Management System under unconstrained video using face recognition technology has made a great variation from the traditional method of attendance marking system. This attendance management system has been developed under the domain of Deep Learning by using Face recognition. Automatic Attendance Management under unconstrained video using face recognition systems which automatically mark attendance by detecting end to end face from the frames obtained from live stream video of surveillance camera which placed in center of the classroom. From the recognized faces, it will be compared with stored images in database, then the attendance report will be generated and it also provides attendance reports to parents of the absentee’s student. 
Keywords:  Automatic Attendance system, Attendance marking, Face recognition, Deep learning.
Scope of the Article: Deep learning.