Capturing Student’s Attendance Using Face Recognition

Open Access

Year : 2023 | Volume : | : | Page : –
By

Maahi Khemchandani,

Hrushikesh Zore,

Siddhant Patil,

Rohan Shinde,

  1. Students, Saraswati College of Engineering, Navi-Mumbai, Maharashtra, India
  2. Students, Saraswati College of Engineering, Navi-Mumbai, Maharashtra, India
  3. Students, Saraswati College of Engineering, Navi-Mumbai, Maharashtra, India
  4. Professor, Saraswati College of Engineering, Navi-Mumbai, Maharashtra, India

Abstract

In instructive foundations, organizations, and different associations, one of the fundamental measures is to keep a record of individuals present every day. Participation Management subsequently turns into a significant objective for the advancement and uprightness of any association. Equipment based participation frameworks that store values in a data set presently exist and are the most well-known record global positioning frameworks found in associations. There are some programmed participations making frameworks that are as of now utilized by numerous foundations. One such framework is the biometric method. Although it is programmed and a stride in front of the customary strategy it neglects to meet the time limitation. The understudy must wait in line for giving participation, which takes time. The proposed framework manages robotizing the participation keep technique in an effective and upgraded way. It follows a counting methodology to keep participation and stores it in the framework. This venture presents a compulsory participation stamping framework, without any sort of impedance with the ordinary instructing method.

Keywords: Face recognition, machine learning, deep learning, face detection, student’s attendance

How to cite this article:
Maahi Khemchandani, Hrushikesh Zore, Siddhant Patil, Rohan Shinde. Capturing Student’s Attendance Using Face Recognition. International Journal of Computer Aided Manufacturing. 2023; ():-.
How to cite this URL:
Maahi Khemchandani, Hrushikesh Zore, Siddhant Patil, Rohan Shinde. Capturing Student’s Attendance Using Face Recognition. International Journal of Computer Aided Manufacturing. 2023; ():-. Available from: https://journals.stmjournals.com/ijcam/article=2023/view=91293


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References

1. Helmi R, Yusuf S, Jamal A. Face recognition automatic class attendance system (FRACAS). IEEE international conference on automatic control and intelligent systems (I2CACIS 2019), Selangor, Malaysia, Jun 29, 2019.
2. Waingankar A, Upadhyay A, Shah R, Pooniwala N, Kasambe P. Face Recognition based Attendance Management System using Machine Learning. Int Res J Eng Technol. 2018;05(06):1979–85.
3. Bhattacharya S, Nainala GS. Prosenjit das and Aurobinda Routray. Smart Attendance Monitoring System (SAMS): A face recognition-based attendance system for classroom environment 18th International Conference on Advanced Learning Technologies. IEEE Publications; 2018. p. 358–60.
4. Chauhan RK, Vivekanand Pandey LM. Smart attendance system using CNN. Int J Pure Appl Math. 2018.
5. Yadav M, Aggarwal A. Motion based attendance system in real time environment for multimedia application; 2018.
6. Liu LL. Human face expression recognition based on deep learning-deep convolutional neural network International Conference on Smart Grid and Electrical Automation (ICSGEA); 2019.
7. Mahajan, KN, Dharwadkar NV. Classroom attendance system using surveillance camera. International Conference on Computer Systems, Electronics and Control, RIT, Islampur, 29th– 30th, January 2016.
8. Varadharajan E, Dharani R, Jeevitha S, Kavinmathi B, Hemalatha S. Automatic attendance management system using face detection. 2016 Online International Conference on Green Engineering and Technologies (IC-GET), 2016, pp. 1–3, doi: 10.1109/GET.2016.7916753.
9. Chitragar VP, Charmore R, Yeshwanthrao M. Smart student attendance management system using face recognition. IJARIIE. 2018;4.
10. Khalel M, Toba AS, Elmogy M. Multimodal student attendance management system. AIN Shams Eng J. December 2018;9(4):2917–29.


Open Access Article
Volume
Received 12/05/2022
Accepted 13/06/2022
Published 13/01/2023