id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-297517-w8cvq0m5	Toğaçar, Mesut	COVID-19 detection using deep learning models to exploit Social Mimic Optimization and structured chest X-ray images using fuzzy color and stacking approaches	2020-05-06		.txt	text/plain	4678	320	58	title: COVID-19 detection using deep learning models to exploit Social Mimic Optimization and structured chest X-ray images using fuzzy color and stacking approaches In this study, the data classes were restructured using the Fuzzy Color technique as a preprocessing step and the images that were structured with the original images were stacked. In the next step, the stacked dataset was trained with deep learning models (MobileNetV2, SqueezeNet) and the feature sets obtained by the models were processed using the Social Mimic optimization method. [9] performed a classification algorithm using pneumonia data, SVM as a classification method, and InceptionV3, VGG-16 models as a deep learning approach. Using pneumonia and normal chest X-ray images, they set 30% of the dataset as test data and compared the proposed approach with the existing CNNs. They achieved 89.57% classification success. The second dataset is important in this study to compare COVID-19 chest images using deep learning models.	./cache/cord-297517-w8cvq0m5.txt	./txt/cord-297517-w8cvq0m5.txt