| JunMa11/MedUncertainty |
251 |
|
0 |
0 |
over 4 years ago |
0 |
|
0 |
|
|
| Uncertainty in Medical Image Analysis |
| kharchenkolab/Baysor |
113 |
|
0 |
0 |
about 2 years ago |
0 |
|
20 |
mit |
Julia |
| Bayesian Segmentation of Spatial Transcriptomics Data |
| ykwon0407/UQ_BNN |
79 |
|
0 |
0 |
over 6 years ago |
0 |
|
0 |
|
Jupyter Notebook |
| Uncertainty quantification using Bayesian neural networks in classification |
| ai-med/quickNAT_pytorch |
75 |
|
0 |
0 |
over 5 years ago |
3 |
July 03, 2018 |
6 |
mit |
Python |
| PyTorch Implementation of QuickNAT and Bayesian QuickNAT, a fast brain MRI segmentation framework with segmentation Quality control using structure-wise uncertainty |
| BGU-CS-VIL/BASS |
65 |
|
0 |
0 |
over 3 years ago |
0 |
|
3 |
mit |
C++ |
| Bayesian Adaptive Superpixel Segmentation (ICCV 2019) |
| ChirikjianLab/Marching-Primitives |
60 |
|
0 |
0 |
almost 3 years ago |
0 |
|
0 |
mit |
MATLAB |
| [CVPR2023 Highlight] Marching-Primitives: Shape Abstraction from Signed Distance Function |
| jacobeisenstein/bayes-seg |
30 |
|
0 |
0 |
over 10 years ago |
0 |
|
3 |
|
Java |
| Java code from the 2008 EMNLP paper "Bayesian Unsupervised Topic Segmentation" by Eisenstein and Barzilay |
| ai-med/nn-common-modules |
22 |
|
0 |
0 |
about 5 years ago |
0 |
|
2 |
mit |
Python |
| Pytorch Implementations of Common modules, blocks and losses for CNNs specifically for segmentation models |
| moucheng2017/EMSSL |
21 |
|
0 |
0 |
almost 3 years ago |
0 |
|
1 |
mit |
Python |
| [MICCAI 2022 Best Paper Finalist] Bayesian Pseudo Labels: Expectation Maximization for Robust and Efficient Semi Supervised Segmentation |
| wiedenhoeft/HaMMLET |
10 |
|
0 |
0 |
about 6 years ago |
0 |
|
2 |
gpl-3.0 |
C++ |
| Fast Bayesian Hidden Markov Model with Wavelet Compression |
