Deep Learning-Based Face Mask Recognition in Real-Time Photos and Videos

Abstract

Our daily lives have seen a significant transformation as a result of COVID-19. The widespread use of face masks as a preventative measure against the virus's spread is one of these modifications. Because of this, face mask detection has become an essential method in many different settings, from public spaces to industrial settings. Face mask detection is a type of computer vision technology that uses machine learning algorithms and artificial intelligence (AI) to detect whether or not a person is wearing a face mask while going about their regular business. The use of cameras and image processing software is common in the use of this technology. These programs analyze still images or video in real time to find situations where people are wearing face masks. Face mask detection is a crucial piece of technology in the fight against COVID-19 and other infectious diseases. One method that this technology can support the implementation of mask-wearing policies and safeguard the public's health and safety is by identifying those who are not wearing masks. Face mask detection is expected to become an increasingly important tool in our efforts to stop the virus from spreading as the world struggles with this epidemic. The proposed approach yields a 95.5% success rate.