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Kernel Clustering: Density Biases and Solutions

IEEE transactions on pattern analysis and machine intelligence, 2019-01, Vol.41 (1), p.136-147

2019

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Boundary loss for highly unbalanced segmentation

Medical image analysis, 2021-01, Vol.67, p.101851-101851, Article 101851

2021

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Kernel Cuts: Kernel and Spectral Clustering Meet Regularization

International journal of computer vision, 2019-05, Vol.127 (5), p.477-511

2019

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Deep Interpretable Classification and Weakly-Supervised Segmentation of Histology Images via Max-Min Uncertainty

IEEE transactions on medical imaging, 2022-03, Vol.41 (3), p.702-714

2022

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Annotation-efficient deep learning for automatic medical image segmentation

Nature communications, 2021-10, Vol.12 (1), p.5915-5915, Article 5915

2021

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Adversarial Robustness Via Fisher-Rao Regularization

IEEE transactions on pattern analysis and machine intelligence, 2023-03, Vol.45 (3), p.2698-2710

2023

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State-of-the-art retinal vessel segmentation with minimalistic models

Scientific reports, 2022-04, Vol.12 (1), p.6174-6174, Article 6174

2022

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Benchmark on Automatic Six-Month-Old Infant Brain Segmentation Algorithms: The iSeg-2017 Challenge

IEEE transactions on medical imaging, 2019-09, Vol.38 (9), p.2219-2230

2019

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Quantitative Identification of Nonmuscle‐Invasive and Muscle‐Invasive Bladder Carcinomas: A Multiparametric MRI Radiomics Analysis

Journal of magnetic resonance imaging, 2019-05, Vol.49 (5), p.1489-1498

2019

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A Strong Baseline for Generalized Few-Shot Semantic Segmentation

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023, p.11269-11278

2023

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An ILP Model for Multi-Label MRFs With Connectivity Constraints

IEEE transactions on image processing, 2020, Vol.29, p.6909-6917

2020

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Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images

NeuroImage (Orlando, Fla.), 2018-12, Vol.183, p.150-172

2018

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HyperDense-Net: A Hyper-Densely Connected CNN for Multi-Modal Image Segmentation

IEEE transactions on medical imaging, 2019-05, Vol.38 (5), p.1116-1126

2019

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Local Submodularization for Binary Pairwise Energies

IEEE transactions on pattern analysis and machine intelligence, 2017-10, Vol.39 (10), p.1985-1999

2017

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3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study

NeuroImage (Orlando, Fla.), 2018-04, Vol.170, p.456-470

2018

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Constrained-CNN losses for weakly supervised segmentation

Medical image analysis, 2019-05, Vol.54, p.88-99

2019

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Exploiting prunability for person re-identification

EURASIP journal on image and video processing, 2021-06, Vol.2021 (1), p.1-31, Article 22

2021

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Few-Shot Segmentation Without Meta-Learning: A Good Transductive Inference Is All You Need?

2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021, p.13974-13983

2021

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High-Order Models in Semantic Image Segmentation

Ben Ayed, Ismail

1, 2023

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Deep CNN ensembles and suggestive annotations for infant brain MRI segmentation

Computerized medical imaging and graphics, 2020-01, Vol.79, p.101660-101660, Article 101660

2020

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Parameter-free Online Test-time Adaptation

2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022, p.8334-8343

2022

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On Regularized Losses for Weakly-supervised CNN Segmentation

Computer Vision – ECCV 2018, p.524-540

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Discretely-constrained deep network for weakly supervised segmentation

Neural networks, 2020-10, Vol.130, p.297-308

2020

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Dense Multi-path U-Net for Ischemic Stroke Lesion Segmentation in Multiple Image Modalities

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, p.271-282

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The Devil is in the Margin: Margin-based Label Smoothing for Network Calibration

2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022, p.80-88

2022

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Kernel Clustering: Density Biases and Solutions

Boundary loss for highly unbalanced segmentation

Kernel Cuts: Kernel and Spectral Clustering Meet Regularization

Deep Interpretable Classification and Weakly-Supervised Segmentation of Histology Images via Max-Min Uncertainty

Annotation-efficient deep learning for automatic medical image segmentation

Adversarial Robustness Via Fisher-Rao Regularization

State-of-the-art retinal vessel segmentation with minimalistic models

Benchmark on Automatic Six-Month-Old Infant Brain Segmentation Algorithms: The iSeg-2017 Challenge

Quantitative Identification of Nonmuscle‐Invasive and Muscle‐Invasive Bladder Carcinomas: A Multiparametric MRI Radiomics Analysis

A Strong Baseline for Generalized Few-Shot Semantic Segmentation

An ILP Model for Multi-Label MRFs With Connectivity Constraints

Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images

HyperDense-Net: A Hyper-Densely Connected CNN for Multi-Modal Image Segmentation

Local Submodularization for Binary Pairwise Energies

3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study

Constrained-CNN losses for weakly supervised segmentation

Exploiting prunability for person re-identification

Few-Shot Segmentation Without Meta-Learning: A Good Transductive Inference Is All You Need?

High-Order Models in Semantic Image Segmentation

Deep CNN ensembles and suggestive annotations for infant brain MRI segmentation

Parameter-free Online Test-time Adaptation

On Regularized Losses for Weakly-supervised CNN Segmentation

Discretely-constrained deep network for weakly supervised segmentation

Dense Multi-path U-Net for Ischemic Stroke Lesion Segmentation in Multiple Image Modalities

The Devil is in the Margin: Margin-based Label Smoothing for Network Calibration

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