Face Mask Detection in Classroom using Deep Convolutional Neural Network

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K.Nithiyasree, et. al.

Abstract

Wearing a mask has become mandatory to protect ourselves from infectious diseases caused by viruses. Today, we are facing a pandemic crisis due to COVID-19 virus. It worsens the lives of living things particularly human beings. The whole world felt stagnant from its normalcy. The educational institutions are particularly affected by this pandemic situation for not conducting the direct classes. To avoid this scenario, they are willing to conduct classes with some guidelines such as social distancing, wearing masks, and sanitizing the hands. We have considered wearing a mask is more important than the remaining two aspects. We are providing a solution with the help of the ResNet50 deep learning network to check whether the students have worn a mask in a classroom in order to prevent them from illness. Deep learning is an advancement of machine learning technique which gives more accurate results than the machine learning algorithms. The performance of our implemented deep learning based face mask detection system is discussed. The live video of the classroom is taken and analysed for recognizing the student’s face with and without mask and generating the name of the students without wearing a mask.

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How to Cite
et. al., K. (2021). Face Mask Detection in Classroom using Deep Convolutional Neural Network. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(10), 1462–1466. Retrieved from https://turcomat.org/index.php/turkbilmat/article/view/4467
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