Real-time Triplet Loss Embedding Face Recognition for Authentication Student Attendance Records System Framework
The number of times students attend lectures has been identified as one of many success factors in the learning process in many studies. We proposed a framework of the student attendance system by using face recognition as authentication. Triplet loss embedding in FaceNet is suitable for face recogn...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Politeknik Negeri Padang
2021-05-01
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| Series: | JOIV: International Journal on Informatics Visualization |
| Subjects: | |
| Online Access: | https://joiv.org/index.php/joiv/article/view/480 |
| _version_ | 1811159785124397056 |
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| author | Hady Pranoto Oktaria Kusumawardani |
| author_facet | Hady Pranoto Oktaria Kusumawardani |
| author_sort | Hady Pranoto |
| collection | DOAJ |
| description | The number of times students attend lectures has been identified as one of many success factors in the learning process in many studies. We proposed a framework of the student attendance system by using face recognition as authentication. Triplet loss embedding in FaceNet is suitable for face recognition systems because the architecture has high accuracy, quite lightweight, and easy to implement in the real-time face recognition system. In our research, triplet loss embedding shows good performance in terms of the ability to recognize faces. It can also be used for real-time face recognition for the authentication process in the attendance recording system that uses RFID. In our study, the performance for face recognition using k-NN and SVM classification methods achieved results of 96.2 +/- 0.1% and 95.2 +/- 0.1% accordingly. Attendance recording systems using face recognition as an authentication process will increase student attendance in lectures. The system should be difficult to be faked; the system will validate the user or student using RFID cards using facial biometric marks. Finally, students will always be present in lectures, which in turn will improve the quality of the existing education process. The outcome can be changed in the future by using a high-resolution camera. A face recognition system with facial expression recognition can be added to improve the authentication process. For better results, users are required to perform an expression instructed by face recognition using a database and the YOLO process. |
| first_indexed | 2024-04-10T05:48:07Z |
| format | Article |
| id | doaj.art-f45832832b0146ddb76e2d9029728a59 |
| institution | Directory Open Access Journal |
| issn | 2549-9610 2549-9904 |
| language | English |
| last_indexed | 2024-04-10T05:48:07Z |
| publishDate | 2021-05-01 |
| publisher | Politeknik Negeri Padang |
| record_format | Article |
| series | JOIV: International Journal on Informatics Visualization |
| spelling | doaj.art-f45832832b0146ddb76e2d9029728a592023-03-05T10:30:14ZengPoliteknik Negeri PadangJOIV: International Journal on Informatics Visualization2549-96102549-99042021-05-015215015510.30630/joiv.5.2.480258Real-time Triplet Loss Embedding Face Recognition for Authentication Student Attendance Records System FrameworkHady Pranoto0Oktaria Kusumawardani1Computer Science Department, School of Computer Science, Bina Nusantara University, Jakarta, 11480, IndonesiaComputer Science Department, School of Computer Science, Bina Nusantara University, Jakarta, 11480, IndonesiaThe number of times students attend lectures has been identified as one of many success factors in the learning process in many studies. We proposed a framework of the student attendance system by using face recognition as authentication. Triplet loss embedding in FaceNet is suitable for face recognition systems because the architecture has high accuracy, quite lightweight, and easy to implement in the real-time face recognition system. In our research, triplet loss embedding shows good performance in terms of the ability to recognize faces. It can also be used for real-time face recognition for the authentication process in the attendance recording system that uses RFID. In our study, the performance for face recognition using k-NN and SVM classification methods achieved results of 96.2 +/- 0.1% and 95.2 +/- 0.1% accordingly. Attendance recording systems using face recognition as an authentication process will increase student attendance in lectures. The system should be difficult to be faked; the system will validate the user or student using RFID cards using facial biometric marks. Finally, students will always be present in lectures, which in turn will improve the quality of the existing education process. The outcome can be changed in the future by using a high-resolution camera. A face recognition system with facial expression recognition can be added to improve the authentication process. For better results, users are required to perform an expression instructed by face recognition using a database and the YOLO process.https://joiv.org/index.php/joiv/article/view/480computer visionface recognitionrecording attendanceframework. |
| spellingShingle | Hady Pranoto Oktaria Kusumawardani Real-time Triplet Loss Embedding Face Recognition for Authentication Student Attendance Records System Framework JOIV: International Journal on Informatics Visualization computer vision face recognition recording attendance framework. |
| title | Real-time Triplet Loss Embedding Face Recognition for Authentication Student Attendance Records System Framework |
| title_full | Real-time Triplet Loss Embedding Face Recognition for Authentication Student Attendance Records System Framework |
| title_fullStr | Real-time Triplet Loss Embedding Face Recognition for Authentication Student Attendance Records System Framework |
| title_full_unstemmed | Real-time Triplet Loss Embedding Face Recognition for Authentication Student Attendance Records System Framework |
| title_short | Real-time Triplet Loss Embedding Face Recognition for Authentication Student Attendance Records System Framework |
| title_sort | real time triplet loss embedding face recognition for authentication student attendance records system framework |
| topic | computer vision face recognition recording attendance framework. |
| url | https://joiv.org/index.php/joiv/article/view/480 |
| work_keys_str_mv | AT hadypranoto realtimetripletlossembeddingfacerecognitionforauthenticationstudentattendancerecordssystemframework AT oktariakusumawardani realtimetripletlossembeddingfacerecognitionforauthenticationstudentattendancerecordssystemframework |