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%.
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