Optimizing the Student Attendance System Using Facial Recognition Technology

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Do Thi Kim Dung1,*, , Huynh Ngoc Tuan1, Le Ngoc Tu1, Le Trung Thanh1
1 University of Phan Thiet

Abstract

 Based on the current digital transformation needs in schools, the facial recognition system for automatic student attendance plays an important role. This system is designed to record students’ entry and exit times, allowing for control over student attendance rather than manual attendance. In this article, the authors study the detection and recognition of faces using algorithms in FaceNet, the triplet loss function, the GAN image enhancement technique, and libraries in Python and CSS programming languages. The group has built an attendance system from the database of images of students created, helping lecturers no longer waste time taking attendance and very convenient in monitoring and statistics of each student’s attendance during the study process at school. 

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How to Cite
Do, T. K. D., Huynh, N. T., Le, N. T., & Le, T. T. (2024). Optimizing the Student Attendance System Using Facial Recognition Technology. The University of Phan Thiet Journal of Science, 2(4), 40-51. https://tapchikhoahocupt.vn/index.php/uptjs/article/view/28
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References

Anitha, G., Devi, P. S., Sri, J. V., & Priyanka, D. (2020). Face Recognition Based Attendance System Using Mtcnn and Facenet. Zeichen, pp. 189-195.

Arjun Raj, A., Shoheb, M., Arvind, K. & Chethan, K. S. (2020). Face Recognition Based Smart Attendance System, International Conference on Intelligent Engineering and Management (ICIEM), pp. 354-355. DOI: 10.1109/ICIEM48762.2020.9160184

Đoàn Hồng Quang, Lê Hồng Minh & Thái Doãn Nguyên (2020). Nhận dạng khuôn mặt trong video bằng mạng nơ ron tích chập = Face recognition in video using convolutional neural network. Tạp chí Khoa học Công nghệ Việt Nam, 1, tr.8 - 12. Truy cập từ http://thuvienlamdong.org.vn:81/handle/DL_134679/28822

Sandberg, D. (2017). Face recognition using Tensorflow. GitHub. Truy cập từ https://github.com/davidsandberg/facenet

Edwin, J. , Greeshma, M., Mithun, H. T. P. & Supriya, M. H. (1019). Face Recognition based Surveillance System Using FaceNet and MTCNN on Jetson TX2. Truy cập từ https://www.researchgate.net/publication/333660229_Face_Recognition_based_Surveillance_System_Using_FaceNet_and_MTCNN_on_Jetson_TX2

Hao Yang & Xiaofeng Han (2020). Face Recognition Attendance System Based on Real-Time Video Processing, IEEE Access, 8, tr.. 159143- 159150. DOI: 10.1109/ACCESS.2020.3007205

Indra, E. (2020). Design and Implementation of Student Attendance System Based on Face Recognition by Haar Like Features Methods. International Conference on Mechanical, Electronics, Computer, and Industrial Technology (MECnIT), tr. 336342, DOI. 10.1109/MECnIT48290.2020.9166595.

Lê Thị Thu Nga, Nguyễn Văn Châu & Nguyễn Xuân Pha (2020). Điểm danh tự động dựa trên mô hình mạng Nơ-Ron tích chập xếp tầng đa nhiệm và kỹ thuật Triplet Loss. Truy cập từ https://elib.vku.udn.vn/bitstream/123456789/764/1/B31.219-226.pdf

Ming, Z., Chazalon, J., Luqman, M. M., Visani, M., & Burie, J. C. (2017). Simple triplet loss based on intra/inter-class metric learning for face verification. International Conference on Computer Vision Workshops (ICCVW), tr.1656-1664. DOI. 10.1109/ICCVW.2017.194

Patil, V., Narayan, A., Ausekar, V. & Dinesh, A. (2020). Automatic students attendance marking system using image processing and machine learning. International Conference on Smart Electronics and Communication (ICOSEC), tr. 542-546. DOI: 10.1109/ICOSEC49089.2020.9215305

Sahu, M. & Dash, R. (2020). Study on Face Recognition Techniques. International Conference on Communication and Signal Processing (ICCSP), tr. 0613-0616, DOI. 10.1109/ICCSP48568.2020.9182358.

Schroff, F., Kalenichenko, D., & Philbin, J. (2015). Facenet: A unified embedding for face recognition and clustering. In Proceedings of the IEEE conference on computer vision and pattern recognition. DOI. 10.1109/CVPR.2015.7298682

Shamila1, M., Bhanu, P., Asrar, A., Poshak, P. & Ruby, P. (2023). Smart Attendance Autiomation System, Department of CSE (AIML), GRIET, Hyderabad, India Uttaranchal Institute of Technology, Uttaranchal University. DOI: 10.1051/e3sconf/202343001019

Shubhobrata Bhattacharya, Gowtham Sandeep Nainala, Prosenjit Das & Aurobinda Routray (2018). Smart Attendance Monitoring System (SAMS): A Face Recognition based Attendance System for Classroom Environment. IEEE 18th International Conference on Advanced Learning Technologies.

Shubhobrata, B., Gowtham, S. N., Prosenjit, D. & Aurobinda, R. (2018). Smart Attendance Monitoring System (SAMS): A Face Recognition based Attendance System for Classroom Environment, IEEE 18th International Conference on Advanced Learning Technologies, tr. 358-360. DOI. 10.1109/ICALT.2018.00090

Smitha, Hegde, Pavithra & Afshin (2020). Face Recognition based Attendance Management System, International Journal of Engineering Research & Technology (IJERT), 9, tr. 1190-1192. DOI:10.17577/IJERTV9IS050861

Weinberger, K.A., Blitzer, J. A., & Saul, L. (2006). Distance metric learning for large margin nearest neighbor classification. In Advances in Neural Information Processing Systems. MIT Press. Truy cập từ https://www.researchgate.net/publication/210341989_Distance_Metric_Learning_for_Large_Margin_Nearest_Neighbor_Classification/citations

Zeiler, M. D. & Fergus. R. (2014). Visualizing and understanding convolutional networks. Truy cập từ https://link.springer.com/chapter/10.1007/978-3-319-10590-1_53