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Updated: Jul 20, 2025

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
08:05

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia

Published on: December 19, 2020

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使用转移学习与视觉几何组和新型序列卷积神经网络进行COVID-19X射线图像的分类

Sunil Kumar1,2, Harish Kumar2

  • 1Department of Information Technology, School of Engineering and Technology (UIET), CSJM University, Kanpur, UP, India.

MethodsX
|August 4, 2023
PubMed
概括

这项研究引入了新的机器学习和深度学习方法,用于从胸部X射线分类COVID-19. 拟议的系统实现了高精度,证明了有效检测COVID-19的潜力.

关键词:
深度学习是一种深度学习.在 LBP LBP 中.机器学习是机器学习.新的序列CNN与使用VGG16和VGG19的转移学习形成对比.在SVM中,SVM是SVM.在VGG16中,VGG16是VGG16中的一个.在VGG19中,VGG19是VGG19的代表.

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