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Journal of Soft Computing Paradigm

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Home / Archives / Volume-3 / Issue-2 / Article-5

Volume - 3 | Issue - 2 | june 2021

Facemask Detection Algorithm on COVID Community Spread Control using EfficientNet Algorithm
Vivekanadam Balasubramaniam  232  163
Pages: 110-122
Cite this article
Balasubramaniam, V. (2021). Facemask Detection Algorithm on COVID Community Spread Control using EfficientNet Algorithm. Journal of Soft Computing Paradigm, 3(2), 110-122. doi:10.36548/jscp.2021.2.005
Published
28 June, 2021
Abstract

Facemask has become mandatory in all COVID-infected communities present across the world. However, in real-life situations, checking the facemask code on each individual has become a difficult task. On the other hand, Automation systems are playing a widespread role in human community to automate different applications. As a result, it necessitates the need to develop a dependable automated method to monitor the facemask code to benefit humans. Recently, deep learning algorithms are emerging as a fast growing application, which has been developed for performing huge number of analysis and detection process. Henceforth, this paper proposes a deep learning based facemask detection process for automating the human effort involved in monitoring process. This work utilizes an openly available facemask detection dataset with 7553 images for the training and verification process, which is based on CNN driven EfficientNet architecture with an accuracy of about 97.12%.

Keywords

Face detection facemask detection COVID 19 CNN EfficientNet

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