Quantifying Model Uncertainty for Semantic Segmentation using Operators in the RKHS

3 November 2022

Papers citing "Quantifying Model Uncertainty for Semantic Segmentation using Operators in the RKHS"

5 / 5 papers shown

Title
Instance-wise Uncertainty for Class Imbalance in Semantic Segmentation Luís Almeida Ines Dutra Francesco Renna UQCV 21 0 0 17 Jul 2024
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam Mohammad Emtiyaz Khan Didrik Nielsen Voot Tangkaratt Wu Lin Y. Gal Akash Srivastava ODL 74 264 0 13 Jun 2018
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
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Robust Semantic Pixel-Wise Labelling Vijay Badrinarayanan Ankur Handa R. Cipolla SSeg 161 783 0 27 May 2015