Face Mask Detection by Using a Novel Detection Model and Machine Learning Analysis
Ms. Karishma B. Shambharkar, Dr. Sudhir W. Mohod, Mr. A. D. Gotmare
Corona Virus, Machine learning analysis, Face Masks, Face mask detection, Image processing, Safety improvement
Since March 2020, the world has been severely impacted by the coronavirus (COVID-19). The primary way that this coronavirus disease propagated was from person to person. Between respiratory droplets that are released when an infected person coughs, sneezes or speaks can spread between people who are in close proximity to one another. People close may get these droplets in their mouths or noses, or they may inhale them and get them in their lungs. Wearing a face mask is one of the precautions to lower the danger of this disease's viral infection, according to studies on the disease. It is required to wear a mask properly in many public and private settings since it can aid to avoid viral transmission. Where clients go to use those services, there are numerous public service providers. Therefore, it is not possible to manually verify whether or not a customer has worn a mask. This issue can be solved through technology. One of the most effective face mask detectors is the one we suggest in this work, which uses machine learning.  Our device has a webcam or cameras built in and can recognize faces with and without masks. This system will assist in preventing safety violations and in maintaining a track of safety.
Article Details
Unique Paper ID: 160742

Publication Volume & Issue: Volume 10, Issue 1

Page(s): 1115 - 1117
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