Published Paper Details:

Corona Virus is a big and dynamic threat to us humans. Now, the whole world is trying to lessen the spread of Covid-19. Wearing masks in a proper way is one of the practices that helps to control the transmission of the virus according to the notable World Health Organization. However, to ensure that all people wear a facemask is a very gigantic task. To prevent the spread of illness, face masks must be used, and cells should be killed or eliminated utilising available therapies such as surgery, radiotherapy, chemotherapy, and others. 30,000 people die each year, according to estimates. Early detection procedures are critical in lowering the mortality rate. X-rays, MRIs, CT scans, ultrasounds, and other imaging techniques are utilised for this. In this research paper, we propose a very simple and effective model for real-time monitoring through the convolution neural of networks to detect if an individual wears a face mask or not. This model is trained, validated, tested upon two datasets. Corresponding to dataset the accuracy of the model was 95.77% and, it was 94.58% for dataset.