Deep Learning-Based Face Mask detection in the Working Scenario of Nuclear Power Plant: Under the Omicron Pandemic

COVID-19 is a great threat to mankind. At present, the world is trying to reduce the spread of the virus. Omicron virus emerged in 2021 and it is much more contagious. This makes it more difficult for humans to stop the spread of the virus, but wearing a mask is a good way to effectively control the Omicron epidemic. According to China’s data, wearing masks has greatly reduced the spread of Omicron. As a national strategic facility, the personnel of the nuclear power plant should pay more attention to protective measures, but it is not easy to ensure that all personnel wear face masks. In order to prevent Omicron from spreading on a large scale in the nuclear power plant and threatening national security. This paper proposes a face mask detection system based on deep learning instead of manual detection, which can detect whether the personnel in the nuclear power plant wear masks as required. At the same time, we developed a new face mask dataset, MASK-N. Our algorithm achieved 0.951 precision on the MASK-N dataset, outperforming all traditional algorithms.