Face Mask Detection by using Optimistic Convolutional Neural Network
K Suresh, M B Palangappa, S Bhuvan
Abstract
COVID-19 pandemic has rapidly increased health crises globally and is affecting our day-to-day lifestyle. A motive for survival recommendations is to wear a safe facemask, stay protected against the transmission of coronavirus. By wearing a facemask, the most effective preventive care must be taken against COVID-19. Monitoring manually if the individuals are wearing facemask correctly and to notify the victim in public and crowded areas is a difficult task. This paper approaches a simplified way to achieve facemask detection and notifying the individual if not wearing facemask. Using Kaggle datasets, the proposed system/model is trained and examined. The system runs in real-time and detects if an individual face has facemask if not then notify the individual personally through text message. The mask is extracted from real-time faces in public and is fed as an input into convolutional neural network (CNN).