id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_z6dwctmg7zd2tjpjeloj4o25mm	Tharun J. Iyer	Performance analysis of lightweight CNN models to segment infectious lung tissues of COVID-19 cases from tomographic images	2021	20	.pdf	application/pdf	7598	956	59	networks are UNet, Segmentation Network (Seg Net), High-Resolution Network Keywords Convolutional neural networks, Computed tomography, COVID-19, Segmentation, High-Resolution Network (HR Net), Segmentation Network (Seg Net), UNet, VGG-UNet segment infectious lung tissues of COVID-19 cases from tomographic images. Existing models works by linking high to low resolution convolutions subnetwork in series, segmentation of each pixel of the image by the model. the True Positive Rate, measures the quality of segmentation of one class and Specificity, or models like HR Net and UNet offer better performance than Inception ResNetV2 and the worst model to use for the Segmentation of COVID-19 based on our study. In this article, we analyzed four models for segmenting COVID-19 from Lung CT Images. Performance analysis of lightweight CNN models to segment infectious lung tissues of COVID-19 cases from tomographic images Performance analysis of lightweight CNN models to segment infectious lung tissues of COVID-19 cases from tomographic images	./cache/work_z6dwctmg7zd2tjpjeloj4o25mm.pdf	./txt/work_z6dwctmg7zd2tjpjeloj4o25mm.txt