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Real-time Face Mask Detection with Face Recognition Using MobileNetV2

Jay Parmar, Hemi Patel

Abstract


In 2019, human civilization faced one of the scariest pandemics in a century. The government advises people to wear a mask for their safety. But there are some cases when we find people without masks,and monitoring all of them manually is not a practical solution in today's world. We needed a method that does this job automatically with higher efficiency. To solve the problem, we have performed face mask detection using deep learning (MobileNetV2 model). We tested our model on live video, and the results are pretty good that our model gives 85–97% accuracy based on video quality and overall accuracy of 97–99%. Enhancement to this feature, we also apply a face recognition library to identify the person who didn't wear a mask; this feature will be useful in an industry where they must monitor their employees.


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References


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