Face Mask Detection Using MobileNet

Abstract

COVID-19 virus is a pandemic that affects the whole world. It is a viral disease that affects almost everyone in one way or another. However, the effect will be different depending on many factors. The global pandemic has affected education and commerce around the world. Many people lose their lives, work, etc. Wearing a mask has become the norm. In the future, COVID-19 will spread very quickly. Everyone needs to wear a mask to avoid this. Therefore, the quest for facial recognition has become an important task to help the world. This article describes the findings of two types of people wearing and not wearing masks. To solve these problems, an automated facial recognition system using machine learning algorithms has effectively managed the spread of COVID-19. We propose a MobileNet-based architecture to detect image descriptions of inappropriate facial expressions. It turned out that someone who was not wearing a mask was detected and a warning was sent. If they do not wear a mask at that time, a fine is sent.