Automatic Face Mask Detection Using Deep Learning
Stephanie Anderson, Suma Veeravenkatappa, Priyanka Pola, Seyedamin Pouriyeh, Meng Han · 2021 IEEE Symposium on Computers and Communications (ISCC) · 2021
COVID-19 shook the entire world with its highly infectious transmission and death rate. As per CDC guidelines, wearing a mask can effectively reduce the spread of COVID-19 and create a protective barrier against the virus until the efficacy of currently available vaccines reaches 100% and the majority of people get vaccinated. Wearing masks is highly recommended almost everywhere, in schools, stores, movies, etc. to prevent the spread of this virus, however, monitoring people to see whether they wear masks is not an easy task. As a result, different face mask detection models were proposed. In this paper, we introduce a face mask detection model using deep learning. We have taken into consideration three different categories to train our model, Mask, No Mask, and Incorrect Mask. The proposed model has achieved 96% accuracy.