Paper Title
Face Mask Detection using Machine Learning
Article Identifiers
: Authors
Keywords
Machine Learning, Computer Vision, Face Mask
Abstract
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%.
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How To Cite (APA)
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
Issue
Volume 8 Issue 7, July-2023
Pages : a246-a249
Other Publication Details
Paper Reg. ID: IJNRD_200894
Published Paper Id: IJNRD2307032
Downloads: 000122033
Research Area: Engineering
Author Type: Indian Author
Country: Pune, Maharashtra, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2307032.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2307032
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