Automated System for Face-Mask Detection Using Convolutional Neural Network

Neha Sengar, Akriti Singh, Saumya Yadav, Malay Kishore Dutta

Abstract: Coronavirus Disease 2019 (COVID-19) pandemic is affecting the health of the global population severely. It is one of the deadliest diseases in history and has severely affected all the countries. The only way to prevent the spread of corona is to cover faces and follow social distancing norms until a vaccine is developed. The face mask is effective in blocking the droplets that contain the COVID-19 virus. Hence, it is necessary to wear a face mask as a precautionary measure against it. In the proposed work, the face mask detection model is generated using an optimized neural network architecture for performing the classification task (mask or no mask). For training and model assessment, a dataset of 8695 images has been taken from four different sources. The model achieves a validation accuracy of 99.52%.