FACE MASK DETECTION USING YOLOV5

Abstract

Amid the ongoing COVID-19 pandemic, wearing face masks in public settings
has been recognized as an effective measure to reduce the spread of the virus by minimizing the
release of respiratory droplets from infected individuals. This study focuses on developing an
efficient method for detecting face masks using a deep learning model based on "Yolov5".
Different models were trained with varying numbers of epochs: 20, 50, 100, 300, and 500.
Experimental findings indicate that the deep learning model trained with 300 epochs achieved
the highest performance, boasting an accuracy of 96.5%..