@inproceedings{latha_soniya_real_2022,
	title = {Real {Time} {Safe} {Social} {Distance} and {Face} {Mask} {Detection} using {YOLO} {Algorithm} and {Deep} {Learning}},
	doi = {10.1109/ICICT54344.2022.9850507},
	abstract = {The pandemic hit the world, and governments all around the world adopted drastic but necessary steps to stop it from spreading may be COVID or other versions. It’s difficult to ensure that individuals follow these important social distance principles in large institutions. An automated system is necessary to enable easy tracking of such offenders. As a result, this system was designed to identify specific infractions in real-time. The proposed system’s initial use is to recognize faces of people to decide whether they are wearing an approved mask or not. The other use is to evaluate whether the social distance is maintained between two people in the most efficient manner that is very accurate, and easy way possible, requiring the least amount of effort from supervisory authorities.},
	booktitle = {2022 {International} {Conference} on {Inventive} {Computation} {Technologies} ({ICICT})},
	author = {Latha Soniya, Pushpa and Velayutham, R},
	month = jul,
	year = {2022},
	note = {ISSN: 2767-7788},
	keywords = {convolutional neural network, deep learning, mentions sympy, real-time systems},
	pages = {528--532},
}

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