基于深度学习的COVID-19口罩检测模型

S. Mohapatra, F. A. Ali, P. Sarangi, Premananda Sahu, J. Mohanty
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引用次数: 0

摘要

新型冠状病毒(Covid-19)在全球,特别是在贫穷国家的不发达国家蔓延后,世界卫生组织(WHO)为了保障社会安全,将其视为危险病毒。由于抗病毒治疗和医疗资源很少,人们应该限制与他人的接触,经常洗手,戴口罩。作为安全程序的一部分,要戴口罩。在全球各地的机场、办公室、购物中心、医院和其他公共场所,每个国家都有执行covid - 19的警察。在这种情况下,医生和其他保健专业人员无法影响病人的健康状况。识别佩戴者的口罩是比人体监测更有效的预防感染方法。Python、深度学习和计算机视觉都被有效地集成到Keras/OpenCV掩码检测器中。将系统的结果与几种掩码检测方法进行比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Deep Learning Based Face Mask Detection Model For COVID-19 Prevention
After the epidemic spread around the globe, particularly in underdeveloped nations in poor countries, the World Health organization (WHO) deemed the Novel Corona Virus (Covid-19) to be a dangerous virus in order to protect social security. People should limit their contact with other people, wash their hands often, and wear masks since there are few antiviral treatments and healthcare resources. As part of the safety procedures, masks are worn. At airports, offices, shopping centres, hospitals, and other public locations around the globe, there are COVID-enforcement police present in every nation. Under these circumstances, doctors and other health professionals are unable to influence patients’ health situations. Identification of the wearer’s face mask is a more effective method of preventing infection than human monitoring. Python, deep learning, and computer vision have all been integrated into this work effectively with Keras/OpenCV mask detector. Examining the outcomes of the system in comparison to several mask detection approaches.
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