DETECTION OF FACE MASK USING DEEP LEARNING

Abstract

As we know, the COVID-19 pandemic additionally referred to as the coronavirus pandemic, is an ongoing pandemic of coronavirus sickness since 2019. This infectious disease was first detected in Wuhan, China in late 2019. Symptoms of COVID-19 are highly variable, ranging from none to severe health problem. The virus spreads chiefly through the air when individuals are close to one another. It transmits from an infected individual through the droplets as they breathe, cough, sneeze or speak and these droplets then enters another individual via their mouth, nose, or eyes. It might also spread via contaminated surfaces. Individuals stay infectious for up to 2 weeks and can spread the virus albeit they do not have symptoms. As of 1st November 2021, more than 200 million cases are confirmed, with more than 500 million deaths due to COVID-19. The pandemic has been the reason for global social and economic disruption, including the largest global recession since the Great Depression. The recommended preventive measures include social distancing, carrying a mask publicly, ventilation and air-filtering, hand washing, covering one‟s mouth when sneezing or coughing and self-isolation for individuals exposed. In present endeavour therefore, the author has attempted to make one thing associated with it, that's deciding whether a dividual is carrying a mask or not. The complete investigations area unit distributed in various chapters that embody the current thesis. The performance of our model will be evaluated in precision, accuracy, recall, specificity, and sensitivity that demonstrate the practical application of this model. The system performs with an accuracy of 99.88%, precision of 99.49%, sensitivity of 99.77%, and specificity of 99.6. Thus, this model tracks if people are using masks or not in real-time using a device camera. This model can be used with the current camera infrastructure to enable this tool which can be used in various public places such as markets or railway stations or offices etc. Keywords: Covid-19, Face Mask Detection, Convolutional Neural Network, MobileNetV2, Precaution.