Detecting A Medical Mask During The COVID-19 Pandemic Using Machine Learning: A Review Study

Mohammed mzeri, L. Ibrahim
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引用次数: 1

Abstract

: Since the emergence of the COVID-19 pandemic, there have been government instructions to citizens to wear a medical mask in crowded places and institutions to prevent or reduce the spread of the pandemic, as the most common method of transmission of COVID-19 is (coughing or sneezing), the spread of infection of this disease can be reduced by wearing a mask Medical , and to ensure that everyone wears a mask is not easy. In this paper, we try to study research in the field of identifying the medical mask and the machine learning algorithms used to build a system capable of detecting the medical mask in faces through images and video in real time. We also explain in this research an overview of the importance of machine learning and deep learning methods, especially Convolutional Neural Network (CNN) and the basic steps for creating the system We reveal the medical mask, and we highlight the methods and stages of building the model with its accuracy and get acquainted with the datasets used in building the model and the size of the data set (number of images) used in the training and testing phase of the model and the mechanism by which The researcher worked out to build his own system.
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在COVID-19大流行期间使用机器学习检测医用口罩:一项综述研究
:自新冠肺炎大流行出现以来,政府已指示公民在拥挤的场所和机构佩戴医用口罩,以防止或减少大流行的传播,因为新冠肺炎最常见的传播方法是(咳嗽或打喷嚏),戴口罩可以减少这种疾病的感染传播,确保每个人都戴口罩并不容易。在本文中,我们试图研究医用口罩识别领域的研究,以及用于构建一个能够通过图像和视频实时检测人脸中医用口罩的系统的机器学习算法。我们还在本研究中概述了机器学习和深度学习方法的重要性,特别是卷积神经网络(CNN)和创建系统的基本步骤,我们强调了建立模型的方法和阶段及其准确性,并熟悉了建立模型时使用的数据集、模型训练和测试阶段使用的数据组大小(图像数量)以及研究人员建立自己系统的机制。
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发文量
38
审稿时长
24 weeks
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