Analysis Of Face Mask Detection During Covid-19 Pandemic

Coronavirus disease 2019 has become a major health problem. It is spreading very widely due to its contact transparent behavior. So WHO declared wearing the mask in crowded areas as a prevention method. In some of the areas, the diseases become widely spread out due to improper wearing of facial masks. So to overcome this problem we required an efficient mask monitoring system. We propose a high- precision and effective MobileFaceMask face- mask detector in this article. It is used in MobileFaceMask is consisting with the Pyramid network, that combines high-quality semantine information, multi- function maps, and a new PC module for facial mask detection. Besides, we propose a new algorithm for the removal of cross-class objects to reject low-confidence predictions and high union intersection. Experiments show that MobileFaceMask delivers good results with 2.3% and 1.5% detection accuracy, while 11.0% and 5.9% more baselines, respectively, are used in a world face mask input dataset. Furthermore, discuss the possibility of deploying MobileFaceMask for embedded or mobile devices with the lightweight MobileNet neural network.