Abstract
The coronavirus (COVID-19) pandemic is an ongoing pandemic of coronavirus disease-2019. It is still spreading continuously across the globe, causing huge economic and social disruption. There are many measures that are suggested by the World Health Organization (WHO) to reduce the spread of this disease. In this paper, we are proposing a system in which people wear masks or not in public and recognize faces who do not wear masks. We detect the people who are monitored by using Webcam and those who are not wearing masks, and the corresponding authority is informed about the same by using convolutional neural network (CNN) with a mobile net and Haar cascade algorithm. The proposed model will help to reduce the spread of the virus and check the safety of surrounding people.
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Shinde, S., Janjal, P., Pawar, G., Rashinkar, R., Rokade, S. (2022). An Automated System for Facial Mask Detection and Face Recognition During COVID-19 Pandemic. In: Agrawal, D.P., Nedjah, N., Gupta, B.B., Martinez Perez, G. (eds) Cyber Security, Privacy and Networking. Lecture Notes in Networks and Systems, vol 370. Springer, Singapore. https://doi.org/10.1007/978-981-16-8664-1_3
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DOI: https://doi.org/10.1007/978-981-16-8664-1_3
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