A Quantitative Comparison of Epistemic Uncertainty Maps Applied to Multi-Class Segmentation

22 September 2021

Papers citing "A Quantitative Comparison of Epistemic Uncertainty Maps Applied to Multi-Class Segmentation"

4 / 4 papers shown

Title
A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation M. Valiuddin R. V. Sloun C.G.A. Viviers Peter H. N. de With Fons van der Sommen UQCV 79 1 0 25 Nov 2024
Influence of uncertainty estimation techniques on false-positive reduction in liver lesion detection Ishaan Bhat J. Pluim M. Viergever Hugo J. Kuijf MedIm 11 4 0 22 Jun 2022
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 268 5,635 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,042 0 06 Jun 2015