Face Recognition Implementation with MTCNN on Attendance System Prototype at Trisakti University

Muhammad Azamy; Anung B. Ariwibowo; Is Mardianto

doi:10.55927/fintech.v1i1.2812

Authors

Muhammad Azamy Trisakti University
Anung B. Ariwibowo Trisakti University
Is Mardianto Trisakti University

DOI:

https://doi.org/10.55927/fintech.v1i1.2812

Keywords:

Face Recognition, MTCNN, Machine Learning, CNN, OpenCV

Abstract

This study aims to implement Face Recognition with MTCNN on Attendance System Prototype at Trisakti University. People work hard to be faster in all parts of life due to the rapid development of technology, which has generated numerous innovations that aid them in their day-to-day tasks. The rapid growth of technology is evident in multiple arenas, including academics. Maintaining the accuracy of attendance data collecting is crucial for all educational institutions because it determines the institution's educational excellence. The word "tipsen" or delegated attendance circulates among academics as an example of data manipulation. To mitigate this, the author attempts to develop a biometric attendance system based on face recognition.

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References

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