Abstract
Since the emergence of the COVID-19 pandemic, there have been government instructions to citizens to wear a medical mask in crowded places and institutions to prevent or reduce the spread of the pandemic, as the most common method of transmission of COVID-19 is (coughing or sneezing), the spread of infection of this disease can be reduced by wearing a mask Medical, and to ensure that everyone wears a mask is not easy. In this paper, we try to study research in the field of identifying the medical mask and the machine learning algorithms used to build a system capable of detecting the medical mask in faces through images and video in real time. We also explain in this research an overview of the importance of machine learning and deep learning methods, especially Convolutional Neural Network (CNN) and the basic steps for creating the system We reveal the medical mask, and we highlight the methods and stages of building the model with its accuracy and get acquainted with the datasets used in building the model and the size of the data set (number of images) used in the training and testing phase of the model and the mechanism by which The researcher worked out to build his own system.
