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Rethinking Bayesian Deep Learning Methods for Semi-Supervised Volumetric Medical Image Segmentation

Rethinking Bayesian Deep Learning Methods for Semi-Supervised Volumetric Medical Image Segmentation

Jianfeng Wang
Thomas Lukasiewicz
    BDL
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Papers citing "Rethinking Bayesian Deep Learning Methods for Semi-Supervised Volumetric Medical Image Segmentation"

5 / 5 papers shown
Title
Rethinking the Mean Teacher Strategy from the Perspective of Self-paced Learning
Rethinking the Mean Teacher Strategy from the Perspective of Self-paced Learning
Pengchen Zhang
Alan J.X. Guo
Sipin Luo
Zhe Han
Lin Guo
34
0
0
16 May 2025
Fixing Overconfidence in Dynamic Neural Networks
Fixing Overconfidence in Dynamic Neural Networks
Lassi Meronen
Martin Trapp
Andrea Pilzer
Le Yang
Arno Solin
BDL
48
16
0
13 Feb 2023
Bidirectional Semi-supervised Dual-branch CNN for Robust 3D Reconstruction of Stereo Endoscopic Images via Adaptive Cross and Parallel Supervisions
Bidirectional Semi-supervised Dual-branch CNN for Robust 3D Reconstruction of Stereo Endoscopic Images via Adaptive Cross and Parallel Supervisions
Hongkuan Shi
Zhiwei Wang
Ying Zhou
Dun Li
Xin Yang
Qiang Li
3DV
34
7
0
15 Oct 2022
Learning with Limited Annotations: A Survey on Deep Semi-Supervised Learning for Medical Image Segmentation
Learning with Limited Annotations: A Survey on Deep Semi-Supervised Learning for Medical Image Segmentation
Rushi Jiao
Yichi Zhang
Leiting Ding
Rong Cai
Jicong Zhang
34
153
0
28 Jul 2022
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
295
9,177
0
06 Jun 2015