Real-Time Face Mask Detection in Mass Gatherings to Reduce Covid-19 Spread

Q4 Engineering
Swapnil Soner, R. Litoriya, Ravi Khatri, Ali Asgar Hussain, Shreyas Pagrey, Sunil Kumar Kushwaha
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引用次数: 0

Abstract

Abstract The Covid 19 (coronavirus) pandemic has become one of the most lethal health crises worldwide. This virus gets transmitted from a person by respiratory droplets when they sneeze or when they speak. According to leading and well-known scientists, wearing face masks and maintaining six feet of social distance are the most substantial protections to limit the virus’s spread. In the proposed model we have used the Convolutional Neural Network (CNN) algorithm of Deep Learning (DL) to ensure efficient real-time mask detection. We have divided the system into two parts—1. Train Face Mask Detector 2. Apply Face Mask Detector—for better understanding. This is a realtime application that is used to discover or detect the person who is wearing a mask at the proper position or not, with the help of camera detection. The system has achieved an accuracy of 99% after being trained with the dataset, which contains around 1376 images of width and height 224×224 and also gives the alarm beep message after the detection of no mask or improper mask usage in a public place.
在大规模集会中实时检测人脸面具,减少 Covid-19 传播
摘要 Covid 19(冠状病毒)大流行已成为全球最致命的健康危机之一。这种病毒通过人打喷嚏或说话时的呼吸道飞沫传播。知名科学家指出,戴口罩和保持六英尺的社交距离是限制病毒传播的最有效保护措施。在提议的模型中,我们使用了深度学习(DL)的卷积神经网络(CNN)算法,以确保高效的实时口罩检测。我们将系统分为两部分--1. 训练人脸面具检测器 2.应用人脸面具检测器,以便更好地理解。这是一个实时应用,用于借助摄像头检测,发现或检测戴口罩的人是否在适当的位置。该系统在使用包含约 1376 幅宽高 224×224 的图像的数据集进行训练后,准确率达到 99%,而且在公共场所检测到没有佩戴口罩或口罩使用不当的情况后还会发出报警提示音。
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来源期刊
Journal of Automation, Mobile Robotics and Intelligent Systems
Journal of Automation, Mobile Robotics and Intelligent Systems Engineering-Control and Systems Engineering
CiteScore
1.10
自引率
0.00%
发文量
25
期刊介绍: Fundamentals of automation and robotics Applied automatics Mobile robots control Distributed systems Navigation Mechatronics systems in robotics Sensors and actuators Data transmission Biomechatronics Mobile computing
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