id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-317643-pk8cabxj	Masud, Mehedi	Convolutional neural network-based models for diagnosis of breast cancer	2020-10-09		.txt	text/plain	4149	276	53	With this motivation, this paper considers eight different fine-tuned pre-trained models to observe how these models classify breast cancers applying on ultrasound images. Authors in [18] proposed a convolutional neural network leveraging Inception-v3 pre-trained model to classify breast cancer using breast ultrasound images. Authors in [24] compared three CNN-based transfer learning models ResNet50, Xception, and InceptionV3, and proposed a base model that consists of three convolutional layers to classify breast cancers from the breast Neural Computing and Applications ultrasound images dataset. Authors in [27] proposed a novel deep neural network consisting of clustering method and CNN model for breast cancer classification using Histopathological images. Then eight different pre-trained models after fine tuning are applied on the combined dataset to observe the performance results of breast cancer classification. This study implemented eight pre-trained CNN models with fine tuning leveraging transfer learning to observe the classification performance of breast cancer from ultrasound images.	./cache/cord-317643-pk8cabxj.txt	./txt/cord-317643-pk8cabxj.txt