Smart Attendance Management System Using Face Recognition

Authors

  • K. V. Prasad Reddy  Associate Professor, Department of Computer Science and Engineering, Sanskrithi School of Engineering, Puttaparthi, Andhra Pradesh, India
  • R. Chaitanya Latha  B.TECH. Scholar, Department of Computer Science and Engineering, Sanskrithi School of Engineering, Puttaparthi, Andhra Pradesh, India
  • M. Lohitha  B.TECH. Scholar, Department of Computer Science and Engineering, Sanskrithi School of Engineering, Puttaparthi, Andhra Pradesh, India
  • R. Sonia  B.TECH. Scholar, Department of Computer Science and Engineering, Sanskrithi School of Engineering, Puttaparthi, Andhra Pradesh, India
  • A. B. Usha  B.TECH. Scholar, Department of Computer Science and Engineering, Sanskrithi School of Engineering, Puttaparthi, Andhra Pradesh, India

DOI:

https://doi.org/10.32628/IJSRST2183162

Keywords:

Attendance Management, Computer Vision, Deep Learning, TkInter.

Abstract

To Maintain the attendance record with day to day activities is a challenging task. The conventional method of calling name of each student is time consuming and there is always a chance of proxy attendance. The smart attendance management will replace the manual method, which takes a lot of time consuming and difficult to maintain. There are many biometric processes, in that face recognition is the best method. Here we are using the computer vision which is a field of deep learning that is used for the camera reading and writing and using TkInter to create a GUI application.

References

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International Journal of Scientific Research in Science and Technology

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Published

2021-06-30

Issue

Volume 8, Issue 3, May-June-2021

Section

Research Articles

License

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
K. V. Prasad Reddy, R. Chaitanya Latha, M. Lohitha, R. Sonia, A. B. Usha "Smart Attendance Management System Using Face Recognition" International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011,Volume 8, Issue 3, pp.706-711, May-June-2021. Available at doi : https://doi.org/10.32628/IJSRST2183162