Authors :
Dr.Anita Harsoor; Ratna; Shriya; Shivani
Volume/Issue :
Volume 7 - 2022, Issue 9 - September
Google Scholar :
https://bit.ly/3IIfn9N
Scribd :
https://bit.ly/3einoZO
DOI :
https://doi.org/10.5281/zenodo.7171741
Abstract :
The COVID-19 Pandemic caused by the new
Corona virus is the cause of this 21st-century global health
crisis. It has forced the government to impose a lockdown
to prevent the transmission of the virus. This led to the
unprecedented shutdown of economic activities. Many
different types of safety measures are being taken in order
to reduce the risk of the spread of this disease at
unprecedented times. Hence, we decided on an approach
that is effective and economic by using deep learning
techniques to create a safe environment in setups such as
manufacturing plants, markets, malls, and other such
places. To demonstrate our approach, the training dataset
is composed of people, the images with and without the
masks, which are collected from a variety of sources and
use it in order to build a robust algorithm in order to
measure the social distance with the help of the classic
geometry methods. We hope that this study will serve as a
useful tool for reducing the spread of this dangerous
infectious disease in the world.
The COVID-19 Pandemic caused by the new
Corona virus is the cause of this 21st-century global health
crisis. It has forced the government to impose a lockdown
to prevent the transmission of the virus. This led to the
unprecedented shutdown of economic activities. Many
different types of safety measures are being taken in order
to reduce the risk of the spread of this disease at
unprecedented times. Hence, we decided on an approach
that is effective and economic by using deep learning
techniques to create a safe environment in setups such as
manufacturing plants, markets, malls, and other such
places. To demonstrate our approach, the training dataset
is composed of people, the images with and without the
masks, which are collected from a variety of sources and
use it in order to build a robust algorithm in order to
measure the social distance with the help of the classic
geometry methods. We hope that this study will serve as a
useful tool for reducing the spread of this dangerous
infectious disease in the world.
