Journal of Pharmaceutical Research International 33 35B 39 45 2021 Article no JPRI 70560 ISSN 2456 9119 Past name British Journal of Pharmaceutical Research Past ISSN 2231 2919 NLM ID 101631759 A Review on COVID 19 Face Mask Detection using CNN Kavita R Singh1 Shailesh D Kamble1 Samiksha M Kalbande1 and Punit Fulzele2 1Computer Science and Engineering Yeshwantrao Chavan College of Engineering Nagpur India 2Department of Pedodontics Sharad Pawar Dental College Secretary Research and Development Jawaharlal Nehru Medical College Datta Meghe Institute of Medical Sciences Sawangi Wardha India Authors contributions This work was carried out in collaboration among all authors All authors read and approved the final manuscript Article Information DOI 10 9734 JPRI 2021 v33i35B31896 Editor s 1 Dr Aurora Mart nez Romero Juarez University Mexico 2 Prof John Yahya I Elshimali Drew University of Medicine and Science USA 3 Dr Ana Cl udia Coelho University of Tr s os Montes and Alto Douro Portugal Reviewers 1 Ihab Layth Hussein Alsammak Directorate General of Education of Karbala Iraq 2 Megha Kamble LNCT Excellence India 3 Ghaidaa A Hafedh Jaber University of Babylon Iraq Complete Peer review History http www sdiarticle4 com review history 70560 Received 04 May 2021 Accepted 05 July 2021 Published 07 July 2021 Review Article ABSTRACT The World Health Organization claims WHO Corona Viruses the COVID 19 pandemic is causing a nationwide crisis wearing a mask on a face in public places is an effective protection measure The COVID 19 pandemic forced governments all over the world to implement quarantine measures in order to deter virus spread Reports suggest that the risk of transmission is clearly minimized by wearing face masks when at work An effective and economic approach to the use of AI in a manufacturing setting to build a secure environment Using a face mask detection dataset we will use Open CV to perform real time face detection from a live stream from our webcam Using Keras Python Tensorflow and Open CV and it will build a COVID 19 face mask detector with computer vision Using computer vision and CNN I aim to decide whether or not the person in the image or video streaming is wear a mask Keywords Deep learning COVID 19 dataset open Cv tensorflow CNN Corresponding author E mail singhkavita19 gmail com WHO to call impelled in 2020 1 INTRODUCTION The COVID 19 corona virus pandemic is causing a worldwide health epidemic As a result the World Health Organization WHO recommends wearing a facemask in public The planet has been seriously the coronavirus infected by outbreak of 2019 One of the main methods of safety for individuals to wear masks in public places and as well maintain social distancing during this crises COVID 19 s accelerated dissemination in 2020 caused the World Health it a national Organization epidemic In computer vision and digital image processing face recognition has become a very common challenge Face masks are becoming more common in public as a result of the global COVID 19 corona virus outbreak Public used to wear a mask on face to shield themselves from airborne diseases air pollution until COVID 19 Scientists have shown that wearing a mask on face acts to inhibit the transmission of COVID 19 COVID 19 is a modern epidemic virus that has infiltrated human health in the last century known as the corona virus The rapid spread of COVID 19 to the WHO announce COVID 19 to be a global epidemic in The corona virus epidemic has resulted levels scientific extraordinary collaboration In a variety of ways Deep Learning and machine learning based Artificial Intelligence can aid in the fight against COVID 19 Machine learning helps scientists and clinicians to evaluate the spread of COVID 19 in vast volumes to serve as an early warning tool for potential pandemics and to categorize species threatened Provision of healthcare needs investment in order to combat and forecast emerging diseases for developing technologies i e IoT artificial intelligence large data and mechanical learning 1 1 Tensorflow TensorFlow is a open source free online software library that covers a range of data flow and differentiated programming practices Google s second generation is used for both research and growth at the company TensorFlow supports 64 bit platforms like like Linux MacOS Windows and smart computing systems Its modular design enables the efficient use of machines across a wide range of platforms TPUs GPUs CPUs from desktops server clusters and smartphones to edge computers framework Tensorflow Ios and Android that are global of to and refers stress reduction Singh et al JPRI 33 35B 39 45 2021 Article no JPRI 70560 The expression TensorFlow the operations performed on multidimensional data panels known as tensors by such neural networks During the Google I O Conference in June2016 Jeff Dean announced that there were 1 500 TensorFlow repositories on GitHub but only 5 were from Google 1 2 Keras Keras is a human centric API not a robot centric one By providing reliable and fast APIs and reducing the number of users tasks required for normal usage Keras follows best practices in cognitive provides understandable and actionable error messages including general documentation and user tutorials Keras provides a range of iterations for widely used building blocks of neural networks such as objectives layers activation functions optimizers and a series of image and text data processing techniques making deep neural code writing simpler GitHub hosts the framework and the mutual aid forums include a GitHub topic tab and Slack site Keras is an easy to use deep learning library for Theano or TensorFlow 1 3 OpenCV GitHub hosts the framework and the mutual aid forums include a GitHub topic tab and Slack site OpenCV was developed to provide a shared vision the inclusion of machine perception in consumer products OpenCV makes for businesses to view and change the code as a BSD licensed application 2 VARIOUS TECHNIQUES OF FACIAL infrastructure and to accelerate it possible MASK DETECTION In 2021 A proposed system to examine the Physical Distance and Mask Wearing on face of building Workers in COVID 19 Pandemic 1 was to developed a computer vision software recognize face masks that automatically wear violations and the physical distance between construction workers to provide protection for the infrastructure projects during the pandemic The document collected and annotated 1 000 images for facial mask