Mandatory Automated Safety Kernel (MASK): Face Mask Recognition Using Deep Learning & Computer Vision

This paper involves utilizing modules to create an efficient and accurate machine learning face mask detection model that can give an accuracy close to 100 percent and a value loss of less than 5%. This paper sees up to the fact that it is the local clusters that need to take care of themselves and this is what will eventually help the society on the larger scale as a whole and aims to aid the concerning authorities in keeping their crowd wearing masks at their respective premises. This is done by programming a system that can recognize the visuals from a camera at the entrance of such premises flagging offenders who do not wear a face mask and notifying authorities as it happens. This can be implemented in private organizations like educational institutions or company offices making it possible to combine it with a facial recognition model thereby notifying the offenders themselves via their cell phones by fetching their information from database resources that would be already existing in the case of these private organizations.