Face Mask Detection using Machine Learning

Registration ID: IJNRD_200894

Published ID: IJNRD2307032

DOI: Click Here to Get

Ankush Mahapatra , Prof. Ajay Talale , Rohan Kulkarni

Machine Learning, Computer Vision, Face Mask

The COVID-19 pandemic had highlighted the need for measures to control the spread of the virus. One of the most effective measures is the use of face masks. In this project, we propose a face mask detection system that utilizes machine learning algorithms to detect whether an individual is wearing a face mask or not. Our system uses Keras, Tensorflow, MobileNet and OpenCV and a dataset of face images with and without masks. We also employ data augmentation techniques such as flipping, rotation, and scaling to increase the size of the training dataset and improve the performance of the model. Our face mask detection system is designed to work in real-world scenarios where lighting conditions and occlusions can be challenging. We also use the MobileNetV2.This architecture is used, it’s also computationally efficient and thus making it easier to deploy the model to embedded systems Our system achieves high accuracy on a public dataset of face images with and without masks. We achieved an accuracy of 98%.

Published Paper   E-Certificate

Ankush Mahapatra, Prof. Ajay Talale, & Rohan Kulkarni (July-2023). Face Mask Detection using Machine Learning. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(7), a246-a249. https://ijnrd.org/papers/IJNRD2307032.pdf

Volume 8 Issue 7, July-2023

Pages : a246-a249

Paper Reg. ID: IJNRD_200894

Published Paper Id: IJNRD2307032

Downloads: 000121992

Research Area: Engineering

Country: Pune, Maharashtra, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2307032.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2307032

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

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

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