Deep Learning Based Facial Mask Detection Using Mobilenetv2

ABSTRACT

The Covid-19 pandemic has had a profound effect on our daily lives. One of the most effective ways to protect ourselves from this virus is to wear face masks. This research paper introduces face mask detection that authorities can use to reduce and prevent COVID-19. The face mask recognition process in this research paper is done with a deep learning algorithm and image processing done using MobileNetV2. Steps to build the model are data collection, pre-processing, data classification, model training and model testing. The authors came up with this approach due to the recent Covid-19 situations for following specific guidelines and the uprising trend of Artificial Intelligence and Machine Learning and its real-world practices. This system has been made to detect more than one person whether they are wearing masks or not. This system also gives us the Covid cases-related worldwide updates as per our chosen country and type of cases like total cases, total deaths etc. Such systems are already available, but the efficiency of the available mask detection systems was not achieved thoroughly. This newly developed system proposes to take a step further, which recognizes more than one person at a time and increases the accuracy level to a much greater extent. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.