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International Research Journal of Engineering and Technology (IRJET)

e-ISSN: 2395-0056

Volume: 09 Issue: 05 | May 2022

p-ISSN: 2395-0072

www.irjet.net

Real Time Face Mask Detection Diya Garg1, Kanika Tyagi2, Juhi Oberoi3, Akanksha Kirola4 Ms . Chhavi Sharma, Dept. of Inderprastha Engineering College, Ghaziabad,India ---------------------------------------------------------------------***---------------------------------------------------------------------

Abstract -CoronaVirus illness (COVID-19) pandemic is

currently a lot more acceptable as a result of it's applied to find faces and to spot people carrying masks in pictures, videos and additionally in period of time vision. By exploiting deep learning and convolution neural network (CNN) techniques, it becomes attainable to achieve high accuracy leads to image classification and object detection applications. making a system for detecting the face-mask can give some way to dominate those that enter any place. The projected system during this paper uses deep learning, TensorFlow, Keras, and OpenCV, that square measure used as a picture classifier to find face-masks.

inflicting a health crisis. One among the effective strategies against the virus is carrying a mask. One o fthe best ways in which to remain safe from obtaining infected is carrying a mask in open territories as indicated by the globe Health Organization (WHO) during this project, we tend to propose a technique that employs TensorFlow and OpenCV to notice face masks on folks. This paper introduces mask detection that may be employed by the authorities to create mitigation, evaluation, prevention, and action designing against COVID-19. The mask recognition during this study is developed with a machine learning formula through the image classification method: MobileNetV2. The steps for building the model square measure collection the information, pre-processing, ripping the information, testing the model, and implementing the model. The engineered model will notice people that square measure carrying a mask and not carrying it at an accuracy of 96.85 percent.

Literature Review Face Mask detection with fine rate Author : R Suganya , SArthi, S Kowshika, V Dhivya Lakshmi. Description : Deep learning technique has been useful for big data analysis and has its applications in computer vision, pattern and speech recognition, etc. A CNN model for speedy face detection has been introduced that evaluates low resolution an input image and discards non-face sections and accurately processes the regions that are at a greater resolution for precise detection. The Face Mask Detection Technology for Image Analysis in the Covid19 Surveillance System Author : G K Jakir Hussain, R Priya , S Rajarajeswari , P Prasanth , N Niyazuddeen. Description : A feasible approach has been proposed that consists of first detecting the face mask region and checking whether persons wear mask or not wear mask and after checking human body temperature using Pc and interrupt to Arduino controller then adding to hand sanitizer. RFID is used for calculating the attendance. Then mask the pc using CNN algorithm.

Key Words: Artificial Intelligence (AI),Machine learning (ML),Deep neural learning(DL),Convolutional Neural Network Model (CNN),Artificial Neural Networks (ANN.)

INTRODUCTION In the shadow of the COVID-19 pandemic, facemask carrying becomes obligatory in many public places throughout the planet, a useful resolution that has verified to be useful in safeguarding these places and reducing the unfold of this pandemic. Several rules square measure set to force carrying a facemask publically and workplaces, which represent hotspots for the unfold of this by not carrying a mask period of time infection. However, not each individual is aware or compliant, therefore risking his or her life and therefore the lives of others watching facemask wearing for an oversized cluster of individuals is becoming a troublesome task. Manual monitoring is normally arduous to enforce because of the men required to efficiently defend public areas and to ensure that people square measure carrying masks correctly except for the value issues and social control effort, the most important downside is the health issue as a result of an exact set of employees are going to be in grips with hundreds of folks daily, that poses a risk of them acting as inflection points, therefore we have a tendency to aim to eliminate the human factor contact after the increase of Covid-19,the Face-Mask detection has been wide considered a retardant within the image processing field. This technology is

Impact Factor value: 7.529

Proposed Approach We decided to build a very simple and basic Convolutional Neural Network (CNN) model using TensorFlow with Keras library and OpenCV to detect if you are wearing a face mask to protect yourself. All the aspects of our work are described below : A. Deep learning design The deep learning design learns varied necessary nonlinear options from the given sample. Then, this learned design is employed to predict antecedently unseen samples.Deep learning is assessed as a joint domain of machine learning. It's a field that takes data from the past and provides the required output through the analysis of advanced pc algorithmic rules.

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