3 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.CV2019
Informative sample generation using class aware generative adversarial networks for classification of chest Xrays
Behzad Bozorgtabar, Dwarikanath Mahapatra, Hendrik von Teng +4
Training robust deep learning (DL) systems for disease detection from medical images is challenging due to limited images covering different disease types and severity. The problem…
cs.CV2017★ 3 cited
Perturb-and-MPM: Quantifying Segmentation Uncertainty in Dense Multi-Label CRFs
Raphael Meier, Urspeter Knecht, Alain Jungo +2
This paper proposes a novel approach for uncertainty quantification in dense Conditional Random Fields (CRFs). The presented approach, called Perturb-and-MPM, enables efficient, ap…