Paper Title
Face Mask Detection Using Image Processing And Deep Learning

Abstract
Wearing a mask is a crucial means of preventing COVID-19 transmission and infection. German researchers found that sporting masks will effectively scale back the infection rate of COVID-19 by four-hundredth. However, the detection of face mask-wearing within the planet is affected by factors like light-weight, occlusion, and multi-object. The detection impact is poor, and the sporting of cotton masks, sponge masks, scarves, and alternative things greatly reduces the personal protection impact. Therefore, this paper proposes a brand new formula for mask detection using machine learning and deep learning. Firstly, we propose a brand new formula for mask detection that integrates deep learning and viola Jones method and Efficient-Yolov3. Secondly, this paper divides mask classification that is wearing a mask or no mask. Experiments on the dataset of with mask or without mask images set show that proposed system includes a higher performance than existing algorithms. Additionally, experiments are performed on the created mask classification knowledge set. The mask classification accuracy of the projected formula is ninety-seven, whereas by existing methodology classification accuracy was 84%. Keywords - Image Processing, Deep Learning