Employee attendance system based on facial recognition

https://doi.org/10.53730/ijhs.v6nS5.9736

Authors

  • Kishore Mukherjee Department of Computer Science and Engineering, K. S. Rangasamy College of Technology, Tiruchengode
  • Manish Kumar Mauriya M Department of Computer Science and Engineering, K. S. Rangasamy College of Technology, Tiruchengode
  • Giridharan Natrajan Assistant Professor, Department of Computer Science and Engineering, K. S. Rangasamy College of Technology, Tiruchengode

Keywords:

One-shot learning, Machine Learning, Face recognition

Abstract

In this digital era, authentication plays a vital role in almost every sector.  From every office related employee to students in educational institutions, authentication is widely used and practiced regularly. Some of the widely used authentications are face recognition, fingerprint recognition, card validation, etc. Face recognition is one of the most used bio-metrics. It can be used for security, authentication, identification, and has got many advantages over other authentication. The current method that institutions and corporate companies uses is the attendance sheet which is signed by the employees and students in their respective institutions. This method sometime disturbs the discipline of the work environment. It is quite a tedious and time- consuming process. There is a need to implement better biometric verification in these institutions that can solve the issue of proxy and time management. But the systems are currently not popular. The solution to these problems is machine learning. Machine learning has attracted huge attention due to its exemplary unique performance and solving a number of complex problems. Due to its training techniques, this technology gained a lot of attention. By using machine learning training method, the image processing has been introduced.

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Published

26-06-2022

How to Cite

Mukherjee, K., Manish, K. M. M. ., & Natrajan, G. (2022). Employee attendance system based on facial recognition. International Journal of Health Sciences, 6(S5), 5054–5069. https://doi.org/10.53730/ijhs.v6nS5.9736

Issue

Section

Peer Review Articles