How's the Turnout to the Class? A Face Detection System for Universities

Savita, K.S.; Hasbullah, Nurul Aini; Taib, Shakirah Mohd; Abidin, Azwar; Muniandy, Manoranjitham

doi:10.1109/ic3e.2018.8632630

Cited by 4 publications

(1 citation statement)

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“…Furthermore, face mask detection refers to the task of finding the location of the face and then detecting masked or unmasked faces [37]. Currently, there are many applications of face recognition and object detection in domains of education [38], autonomous driving [39], surveillance and so on [40].…”

Section: Introductionmentioning

confidence: 99%

An Automated Real-Time Face Mask Detection System Using Transfer Learning with Faster-RCNN in the Era of the COVID-19 Pandemic

Sabir¹,

Mehmood²,

Alsaggaf³

et al. 2022

Computers, Materials &Amp; Continua

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Today, due to the pandemic of COVID-19 the entire world is facing a serious health crisis. According to the World Health Organization (WHO), people in public places should wear a face mask to control the rapid transmission of COVID-19. The governmental bodies of different countries imposed that wearing a face mask is compulsory in public places. Therefore, it is very difficult to manually monitor people in overcrowded areas. This research focuses on providing a solution to enforce one of the important preventative measures of COVID-19 in public places, by presenting an automated system that automatically localizes masked and unmasked human faces within an image or video of an area which assist in this outbreak of COVID-19. This paper demonstrates a transfer learning approach with the Faster-RCNN model to detect faces that are masked or unmasked. The proposed framework is built by fine-tuning the state-of-the-art deep learning model, Faster-RCNN, and has been validated on a publicly available dataset named Face Mask Dataset (FMD) and achieving the highest average precision (AP) of 81% and highest average Recall (AR) of 84%. This shows the strong robustness and capabilities of the Faster-RCNN model to detect individuals with masked and un-masked faces. Moreover, this work applies to real-time and can be implemented in any public service area.

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