Calibrating the Dice loss to handle neural network overconfidence for
biomedical image segmentation

Calibrating the Dice loss to handle neural network overconfidence for biomedical image segmentation

31 October 2021

Carola-Bibiane Schönlieb

Guang Yang

Papers citing "Calibrating the Dice loss to handle neural network overconfidence for biomedical image segmentation"

10 / 10 papers shown

Title
Occlusion-Ordered Semantic Instance Segmentation Soroosh Baselizadeh Cheuk-To Yu O. Veksler Yuri Boykov ISeg 3DV 54 0 0 18 Apr 2025
We Care Each Pixel: Calibrating on Medical Segmentation Model Wenhao Liang W. Zhang Y. Lin Miao Xu Olaf Maennel Weitong Chen 38 0 0 07 Mar 2025
HairFastGAN: Realistic and Robust Hair Transfer with a Fast Encoder-Based Approach Maxim Nikolaev Mikhail Kuznetsov Dmitry Vetrov Aibek Alanov 3DH 16 5 0 01 Apr 2024
Average Calibration Error: A Differentiable Loss for Improved Reliability in Image Segmentation Theodore Barfoot Luis C. García-Peraza-Herrera Ben Glocker Tom Vercauteren UQCV 30 2 0 11 Mar 2024
RIDGE: Reproducibility, Integrity, Dependability, Generalizability, and Efficiency Assessment of Medical Image Segmentation Models Farhad Maleki Linda Moy Reza Forghani Tapotosh Ghosh K. Ovens ... Atlas Haddadi Avval S. Sotardi Neil Tenenholtz Felipe Kitamura Timothy Kline 20 0 0 16 Jan 2024
A Survey of Computer Vision Technologies In Urban and Controlled-environment Agriculture Jiayun Luo Boyang Albert Li Cyril Leung 35 10 0 20 Oct 2022
Trustworthy clinical AI solutions: a unified review of uncertainty quantification in deep learning models for medical image analysis Benjamin Lambert Florence Forbes A. Tucholka Senan Doyle Harmonie Dehaene M. Dojat 11 74 0 05 Oct 2022
Unified Focal loss: Generalising Dice and cross entropy-based losses to handle class imbalanced medical image segmentation Michael Yeung Evis Sala Carola-Bibiane Schönlieb L. Rundo 23 387 0 08 Feb 2021
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