3.3k citations · 3.3k across the 2 of their papers we have counts for
3 papers
Active, Continual Fine Tuning of Convolutional Neural Networks for Reducing Annotation Efforts
Zongwei Zhou, Jae Y. Shin, Suryakanth R. Gurudu +2
The splendid success of convolutional neural networks (CNNs) in computer vision is largely attributable to the availability of massive annotated datasets, such as ImageNet and Plac…
Automating Carotid Intima-Media Thickness Video Interpretation with Convolutional Neural Networks
Jae Y. Shin, Nima Tajbakhsh, R. Todd Hurst +2
Cardiovascular disease (CVD) is the leading cause of mortality yet largely preventable, but the key to prevention is to identify at-risk individuals before adverse events. For pred…
Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?
Nima Tajbakhsh, Jae Y. Shin, Suryakanth R. Gurudu +4
Training a deep convolutional neural network (CNN) from scratch is difficult because it requires a large amount of labeled training data and a great deal of expertise to ensure pro…