基于深度学习的COVID-19协议违规实时检测

Proceedings of the 2022 Fourteenth International Conference on Contemporary Computing Pub Date : 2022-08-04 DOI:10.1145/3549206.3549282

N. Singh, Anurag Goel

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引用次数: 0

摘要

自过去几年以来，COVID-19大流行在全球范围内造成了严重的卫生紧急情况，并且在少数国家仍在出现。根据世界卫生组织(世卫组织)的数据，截至2022年5月19日撰写本文，已报告了约5.2亿例COVID-19病例和620万人伤亡。世界上几乎所有国家都实施了包括戴口罩和保持社交距离在内的COVID-19协议。实时跟踪人们对COVID-19协议的遵守情况是一项挑战。本文提出了一种实时检测COVID-19协议违规的模型。我们还创建了一个web应用程序，该应用程序使用所提出的模型实时检测COVID-19协议的遵守情况。该模型在包含1376张图像的数据集上进行了测试，即使在复杂的环境下也显示出令人满意的结果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Detection of COVID-19 Protocols Violation in Real Time using Deep Learning

COVID-19 pandemic has created a severe health emergency all over the globe since last couple of years and is still emerging in few countries. According to the World Health Organization (WHO), around 520 million cases and 6.2 million casualties due to COVID-19 have been reported till the writing of this manuscript, 19th May 2022. The COVID-19 protocols including wearing masks, following social distancing have been imposed in almost all the countries worldwide. It is a challenge to track the adherence of the COVID-19 protocols by the people in real time. This work proposes a model for the detection of COVID-19 protocols violation in real time. We have also created a web application which uses the proposed model to detect the adherence of COVID-19 protocols in real time. The proposed model is tested on a dataset comprises of 1376 images and has shown promising results even in complex environment.

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Proceedings of the 2022 Fourteenth International Conference on Contemporary Computing

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