Real-Time Face Mask Detection by Clever Convolution Neural Networks

EasyChair Preprint 9188

Abstract

Face Mask Detection is the process of determining if a mask is being worn by a person or not. Our paper's purpose is to determine whether someone is wearing a mask properly or not. When a mask entirely covers a person's mouth and nose, he is wearing it correctly. Conferring to the current works, relatively little study has been done to identify masks over faces. There by, the goal of our work is to develop a technology that can detect masks over the face in public facilities in order to avert the spread of COVID-19 accurately and thus contribute to public welfare. This paper proposes a simpler approach to accomplish this goal utilizing some libraries such as TensorFlow, Keras, etc. We investigate optimum parameter values utilizing the YOLO (You Only Look Once) technique. COVID-19 pandemic has a significant impact on the society, causing global trade and transportation to be disrupted

Keyphrases: Pre-processing, YOLO, data augmentation, image segmentation, object detection

@booklet{EasyChair:9188,
  author    = {Suresh Kumar Kanaparthi and Sai Pratheeka Kaluvala and Vyshnavi Ravula and Jyothika Sai Masimukkula and Sri Indu Dekkapati},
  title     = {Real-Time Face Mask Detection by Clever Convolution Neural Networks},
  howpublished = {EasyChair Preprint 9188},
  year      = {EasyChair, 2022}}