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I. Covid-19 Detection using Deep Learning Models

机译:I. Covid-19使用深度学习模型进行检测

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摘要

The outbreak of Corona disease, or the so-called Covid-19, has affected the course of human life. Detecting this disease early reduces the risk of spreading the disease. Thus, get rid of this epidemic sooner. In this paper, a system is created that helps to identify and detect Covid-19 disease through X-ray radiation. GoogLeNet, ResNet-101, Inception v3 network, and DAG3Net that are used for comparison purposes. Good results have been obtained in detecting Covid-19 disease, where the DAG3Net produces diagnostic (validation, training, testing and overall) accuracies of (96.15%, 94.34%, 96.75% and 96.58%) respectively, while the GoogLeNet, ResNet-101, and Inception v3 network are produced (98.08%, 100%, 99.59% and 99.72%) respectively.
机译:爆发了电晕疾病,或所谓的Covid-19,影响了人类生活的过程。 检测到这种疾病早期降低了扩散疾病的风险。 因此,早早摆脱这种流行病。 在本文中,创建了一种系统,其有助于通过X射线辐射识别和检测Covid-19疾病。 Googlenet,Reset-101,Inception V3网络和用于比较目的的DAG3Net。 在检测Covid-19疾病中获得了良好的结果,其中DAG3Net分别产生(96.15%,94.34%,96.75%和96.58%)的诊断(验证,培训,测试和整体),而Googlenet resnet-101 而且分别产生了v3网络(98.08%,100%,99.59%和99.72%)。

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