REAL TIME FACE MASK DETECTION AND ACCURACY PREDICTION

Sanapala Anusha , Reddy Harithasri , Samardi Preethi , Sappa Prameela , Dr.P.Himakeerthi

Open cv, mask Detection,OpenCV Library,Image Recognition,Tensor Flow, Convolutional Neural Network,python,machine learning

Wearing a face mask appears to be important to both the person and other people to restrict the spread of a virulent disease that can be communicated via sputtering in the context of a virulent sickness which can be transmitted via sputtering. During the COVID-19 pandemic, people all around the world were required to wear masks to limit the danger of virus transmission. According to research, properly wearing a face mask can effectively reduce transmission and save lives. The identification of face masks has made significant progress in the domains of image processing and computer vision since the start of the Covid-19 pandemic. Face recognition models have been built using a number of algorithms and methodologies. This is a deep learning model design using Python, TensorFlow, Keras, MobileNet, and openCV in this project. The main goal is to utilise a trained AI model and a collection of masked and unmasked photos to determine whether or not someone is wearing a mask during a webcam Livestream. Because it is relatively resource efficient to deploy, this model can be employed for safety considerations

Published Paper   E-Certificate

"REAL TIME FACE MASK DETECTION AND ACCURACY PREDICTION", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 3, page no.c706-c711, March-2023, Available :https://ijnrd.org/papers/IJNRD2303279.pdf

Volume 8 Issue 3, March-2023

Pages : c706-c711

Paper Reg. ID: IJNRD_189083

Published Paper Id: IJNRD2303279

Downloads: 000118853

Research Area: Computer Science & Technology 

Country: Srikakulam, Andhra Pradesh, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2303279

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2303279

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition