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Automatic attendance system using face recognition with deep learning algorithm

This project aims to develop an attendance system that is more efficient and convenient than traditional attendance methods currently used in schools and universities. Therefore, this paper proposes an automatic attendance system using face recognition. In this face recognition attendance system, th...

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Main Authors: Al-Amoudi, Ibrahim, Rosdiyana, Samad, Nor Rul Hasma, Abdullah, Mahfuzah, Mustafa, Pebrianti, Dwi
Format: Conference or Workshop Item
Language:English
English
Published: Springer Science and Business Media Deutschland GmbH 2022
Subjects:
T Technology (General)
TA Engineering (General). Civil engineering (General)
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/39736/1/Automatic%20Attendance%20System%20Using%20Face%20Recognition%20with%20Deep.pdf
http://umpir.ump.edu.my/id/eprint/39736/2/Automatic%20attendance%20system%20using%20face%20recognition%20with%20deep%20learning%20algorithm_ABS.pdf
http://umpir.ump.edu.my/id/eprint/39736/
https://doi.org/10.1007/978-981-16-2406-3_44
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spelling my.ump.umpir.397362023-12-22T08:33:17Z http://umpir.ump.edu.my/id/eprint/39736/ Automatic attendance system using face recognition with deep learning algorithm Al-Amoudi, Ibrahim Rosdiyana, Samad Nor Rul Hasma, Abdullah Mahfuzah, Mustafa Pebrianti, Dwi T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering This project aims to develop an attendance system that is more efficient and convenient than traditional attendance methods currently used in schools and universities. Therefore, this paper proposes an automatic attendance system using face recognition. In this face recognition attendance system, the university does not need to install any additional devices in the classroom, which makes it a cost-effective system. The system consists of three parts: attendance system, student profile system, and training. First is the training stage where the student’s photo should be captured and stored in a separate folder. Second is the attendance system. Here the lecturer needs to take a photograph of the student and then upload it to the system. The system will automatically recognize the student’s face and store his/her name in an excel sheet (CVS file). The third system is the student’s profile. This system is to help the lecturer retrieve the student’s data by only capturing a picture of the student. A GUI has been made to simplify the usage of the system. The face recognition system has been developed using a combination of two deep learning algorithms: Multi-Task Cascaded Convolutional Neural Network (MTCNN) and FaceNet. To train the system, 908 pictures from 21 different students were collected and used, and 108 pictures were used for testing. The testing result showed 100% for face detection and 87.03% for face recognition. Springer Science and Business Media Deutschland GmbH 2022 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/39736/1/Automatic%20Attendance%20System%20Using%20Face%20Recognition%20with%20Deep.pdf pdf en http://umpir.ump.edu.my/id/eprint/39736/2/Automatic%20attendance%20system%20using%20face%20recognition%20with%20deep%20learning%20algorithm_ABS.pdf Al-Amoudi, Ibrahim and Rosdiyana, Samad and Nor Rul Hasma, Abdullah and Mahfuzah, Mustafa and Pebrianti, Dwi (2022) Automatic attendance system using face recognition with deep learning algorithm. In: Lecture Notes in Electrical Engineering; 12th National Technical Seminar on Unmanned System Technology, NUSYS 2020 , 24-25 November 2020 , Virtual, Online. pp. 573-588., 770 (266059). ISSN 1876-1100 ISBN 978-981162405-6 https://doi.org/10.1007/978-981-16-2406-3_44
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
English
topic T Technology (General)
TA Engineering (General). Civil engineering (General)
TK Electrical engineering. Electronics Nuclear engineering
spellingShingle T Technology (General)
TA Engineering (General). Civil engineering (General)
TK Electrical engineering. Electronics Nuclear engineering
Al-Amoudi, Ibrahim
Rosdiyana, Samad
Nor Rul Hasma, Abdullah
Mahfuzah, Mustafa
Pebrianti, Dwi
Automatic attendance system using face recognition with deep learning algorithm
description This project aims to develop an attendance system that is more efficient and convenient than traditional attendance methods currently used in schools and universities. Therefore, this paper proposes an automatic attendance system using face recognition. In this face recognition attendance system, the university does not need to install any additional devices in the classroom, which makes it a cost-effective system. The system consists of three parts: attendance system, student profile system, and training. First is the training stage where the student’s photo should be captured and stored in a separate folder. Second is the attendance system. Here the lecturer needs to take a photograph of the student and then upload it to the system. The system will automatically recognize the student’s face and store his/her name in an excel sheet (CVS file). The third system is the student’s profile. This system is to help the lecturer retrieve the student’s data by only capturing a picture of the student. A GUI has been made to simplify the usage of the system. The face recognition system has been developed using a combination of two deep learning algorithms: Multi-Task Cascaded Convolutional Neural Network (MTCNN) and FaceNet. To train the system, 908 pictures from 21 different students were collected and used, and 108 pictures were used for testing. The testing result showed 100% for face detection and 87.03% for face recognition.
format Conference or Workshop Item
author Al-Amoudi, Ibrahim
Rosdiyana, Samad
Nor Rul Hasma, Abdullah
Mahfuzah, Mustafa
Pebrianti, Dwi
author_facet Al-Amoudi, Ibrahim
Rosdiyana, Samad
Nor Rul Hasma, Abdullah
Mahfuzah, Mustafa
Pebrianti, Dwi
author_sort Al-Amoudi, Ibrahim
title Automatic attendance system using face recognition with deep learning algorithm
title_short Automatic attendance system using face recognition with deep learning algorithm
title_full Automatic attendance system using face recognition with deep learning algorithm
title_fullStr Automatic attendance system using face recognition with deep learning algorithm
title_full_unstemmed Automatic attendance system using face recognition with deep learning algorithm
title_sort automatic attendance system using face recognition with deep learning algorithm
publisher Springer Science and Business Media Deutschland GmbH
publishDate 2022
url http://umpir.ump.edu.my/id/eprint/39736/1/Automatic%20Attendance%20System%20Using%20Face%20Recognition%20with%20Deep.pdf
http://umpir.ump.edu.my/id/eprint/39736/2/Automatic%20attendance%20system%20using%20face%20recognition%20with%20deep%20learning%20algorithm_ABS.pdf
http://umpir.ump.edu.my/id/eprint/39736/
https://doi.org/10.1007/978-981-16-2406-3_44
_version_ 1822924005270618112
score 13.232414

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