id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-269873-4hxwo5kt	R., Mohammadi	Transfer Learning-Based Automatic Detection of Coronavirus Disease 2019 (COVID-19) from Chest X-ray Images	2020-10-01		.txt	text/plain	3378	199	52	OBJECTIVE: This study aimed to use an automated deep convolution neural network based pre-trained transfer models for detection of COVID-19 infection in chest X-rays. MATERIAL AND METHODS: In a retrospective study, we have applied Visual Geometry Group (VGG)-16, VGG-19, MobileNet, and InceptionResNetV2 pre-trained models for detection COVID-19 infection from 348 chest X-ray images. To this end, the present study aimed to use an automated deep convolution neural network based pre-trained transfer models for detection and diagnosis of COVID-19 infection in chest X-rays. In this study, a CNN-based model was used to detect COVID-19 from the chest X-ray images. In this study, we proposed four pre-trained deep CNN models, including VGG-16, VGG-19, MobileNet, and InceptionResNetV2 for discriminating COVID-19 cases from chest X-ray images. In this study, we presented four pre-trained deep CNN models such as VGG16, VGG19, MobileNet, and InceptionResNetV2 are used for transfer learning to detect and classify COVID-19 from chest radiography.	./cache/cord-269873-4hxwo5kt.txt	./txt/cord-269873-4hxwo5kt.txt