Screening Medical Face Mask for Coronavirus Prevention using Deep Learning and AutoML
Oussama El Gannour, Bouchaib Cherradi, Soufiane Hamida, Mohammed Jebbari, Abdelhadi Raihani · 2022 2nd International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET) · 2022
In the last two years, the COVID-19 pandemic causes a global health crisis around the world. On the other hand, given the current shortage and limits of medical resources, the World Health Organization (WHO) suggests several measures to control the infection rate and avoid depleting limited medical resources. In fact, wearing a medical mask is one of the non-pharmaceutical measures that can be used to limit the spread of this pandemic. This paper aims to present a new deep learning model based on AutoML for medical face mask detection. This proposed model was trained on a publicly available dataset that contained three classes: With mask, Incorrect mask, and Without mask. The achieved results show that the proposed model reaches an Accuracy and sensitivity of 99.74% and 99% respectively.