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  1. University of Information Technology
  2. Faculty of Computer Science

University Classroom Attendance System Using Face Recognition Technique

http://hdl.handle.net/20.500.12678/0000006189
http://hdl.handle.net/20.500.12678/0000006189
b3a53dcf-8cad-4054-a6d2-c1cb62863489
c2a1fc11-872e-4d5b-ad41-02f7e119925c
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University University Classroom Attendance System Using Face Recognition Technique.pdf (373 Kb)
Publication type
Journal article
Upload type
Publication
Title
Title University Classroom Attendance System Using Face Recognition Technique
Language en
Publication date 2019-10-01
Authors
Thida Nyein
Aung Nway Oo
Description
There are rules and principles to obey for everywhere. And also there are various rules to obey for every staff, students and teachers in every University. Among many rules, each student must be full the defined the attendance record percentage. The attendance record is an important role for the evaluation of each student for classroom participation. For instance, if the attendance of the lecture must be full 75 percentage for each subject, it defines that the student can perform in exam well and can know well for that subject. So, only the students having at least 75 percentage attendance can sit the exam. There are many ways to take the attendance record. Nowadays, the attendance management system is by using QR code, fingerprint recognition, face recognition, etc. And also, in many applications, face recognition become popular to use and it is used for tracing the criminals, for payment, for access right and for taking the attendance because it is reliable, convenience, inexpensive, and easy to use. This proposed system is the classroom automatic attendance system for the University by using face recognition technique Deep Learning technique is used for this system. CNN (Convolutional neural network) is one of deep neural networks. There are many famous CNN models (LeNet, AlexNet, GoogleNet, VGGNet, ResNet, FaceNet, etc). In the proposed system, FaceNet is used for feature extraction and Support vector machine is used for face classification of students. The result of proposed system is compared to the results of RestNet model. The proposed system can be used to reduce time consuming and paper works and can also replace the manual system with the automated attendance system.
Keywords
deep learning, face recognition, FaceNet, convolutional neural network, support vector machine, ResNet
Journal articles
UJRI
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