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Face Mask Detection Using Deep Learning and Computer Vision

Authors:

M.Kumaresan, Shreya Kumari, Kunal Kumar Munda ,B.Venkata Sai Ranga Reddy

Abstract— Automated monitoring of face mask compliance has become essential in public health, especially since the COVID-19 pandemic. Manual enforcement is inefficient in crowded places. This paper proposes a real-time face mask detection system based on deep learning and computer vision. A convolutional neural network (CNN) is trained on a diverse dataset to distinguish between masked and unmasked faces in images and video streams. The system achieved a test accuracy of 97.3% and remained robust under diverse lighting, angles, and partial occlusions. Designed for efficiency, the solution operates in real-time on standard hardware, making it suitable for public health surveillance, access control, and smart monitoring. The implementation is open-source and accessible at GitHub.

Keywords—Face Mask Detection, Deep Learning, Computer Vision, CNN, COVID-19, Real-time Monitoring