DOIONLINE

DOIONLINE NO - IJACEN-IRAJ-DOIONLNE-17153

Publish In
International Journal of Advance Computational Engineering and Networking (IJACEN)-IJACEN
Journal Home
Volume Issue
Issue
Volume-8,Issue-5  ( May, 2020 )
Paper Title
Location Enabled Effective Student Attendance Monitoring System using Feature Searching and Convolutional Neural Network
Author Name
Neha Mayekar, Shreya Pattewar, Shubham Patil, Ajay Dhruv
Affilition
Student, Vidyalankar Institute of Technology, Mumbai, India Assistant Professor, Vidyalankar Institute of Technology, Mumbai, India
Pages
20-24
Abstract
In this era of the 21st' century, classroom attendance is very important in almost all colleges. Classroom attendance can effectively supervise students to attend classes on time and ensure the quality of classroom learning. However, without attending lectures, students' attendance is up to date because of proxies. Another problem in college is if students have some doubts, they search for a teacher in the staff room if the teacher is not available in the staff room then finding a teacher in college is a very difficult job. In this paper, solution is proposed which makes use of facial features of the students. Keywords - Attendance, Effective Student Attendance Monitoring System (ESAM), Face Recognition, Image Processing, Machine Learning.
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