| Issue |
ITM Web Conf.
Volume 74, 2025
International Conference on Contemporary Pervasive Computational Intelligence (ICCPCI-2024)
|
|
|---|---|---|
| Article Number | 01012 | |
| Number of page(s) | 10 | |
| Section | Artificial Intelligence and Machine Learning Applications | |
| DOI | https://doi.org/10.1051/itmconf/20257401012 | |
| Published online | 20 February 2025 | |
Enhanced Attendance Management of Face Recognition Using Machine Learning
1,2,3,4 Department of CSE, Vignan’s Foundation for Science, Technology and Research Vadlamudi, Guntur, Andhra Pradesh, India
5 Department of Computer Science and Engineering, Vignan’s Foundation for Science, Technology and Research, Vadlamudi, Guntur, Andhra Pradesh, India
Conventional attendance tracking has been very timeconsuming, error-prone, and often requires a certain amount of human input and verification. Automating such solutions by using face recognition technology has thus become a viable way to deal with these problems. Our approach does not require pre-registered datasets since it automatically captures and identifies faces from a live camera stream using machine learning to automate attendance. In the alternative, real-time training takes place on location with on-location photos, thereby allowing the system to adapt to specific conditions including lighting variations, subtle facial planes, and even expressions. This results in excellent accuracy and consistency for use in all kinds of scenarios, such as offices, learning institutions, or events.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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