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ORCIDHervé Lombaert
- > Home > Persons > Hervé Lombaert
Publications
- 2024
[j16]Sukesh Adiga V
, Jose Dolz, Herve Lombaert:
Anatomically-aware uncertainty for semi-supervised image segmentation. Medical Image Anal. 91: 103011 (2024)- [i27]Balamurali Murugesan, Sukesh Adiga Vasudeva, Bingyuan Liu, Hervé Lombaert, Ismail Ben Ayed, Jose Dolz:
Neighbor-Aware Calibration of Segmentation Networks with Penalty-Based Constraints. CoRR abs/2401.14487 (2024) - 2023
- [c43]Balamurali Murugesan, Sukesh Adiga V, Bingyuan Liu, Herve Lombaert, Ismail Ben Ayed, Jose Dolz:
Trust Your Neighbours: Penalty-Based Constraints for Model Calibration. MICCAI (3) 2023: 572-581 - [c42]Sukesh Adiga Vasudeva, Jose Dolz, Herve Lombaert:
GeoLS: Geodesic Label Smoothing for Image Segmentation. MIDL 2023: 468-478 - [i22]Balamurali Murugesan, Sukesh Adiga V, Bingyuan Liu, Hervé Lombaert, Ismail Ben Ayed, Jose Dolz:
Trust your neighbours: Penalty-based constraints for model calibration. CoRR abs/2303.06268 (2023) - [i21]Sukesh Adiga V, Jose Dolz, Herve Lombaert:
Anatomically-aware Uncertainty for Semi-supervised Image Segmentation. CoRR abs/2310.16099 (2023) - 2022
- [j12]Mathilde Bateson, Hoel Kervadec, Jose Dolz, Hervé Lombaert, Ismail Ben Ayed:
Source-free domain adaptation for image segmentation. Medical Image Anal. 82: 102617 (2022) - [j10]Sukesh Adiga V, Jose Dolz, Herve Lombaert:
Attention-Based Dynamic Subspace Learners for Medical Image Analysis. IEEE J. Biomed. Health Informatics 26(9): 4599-4610 (2022) - [c39]Sukesh Adiga V, Jose Dolz, Herve Lombaert:
Leveraging Labeling Representations in Uncertainty-Based Semi-supervised Segmentation. MICCAI (8) 2022: 265-275 - [i20]Sukesh Adiga V, Jose Dolz, Herve Lombaert:
Leveraging Labeling Representations in Uncertainty-based Semi-supervised Segmentation. CoRR abs/2203.05682 (2022) - [i18]Sukesh Adiga V, Jose Dolz, Herve Lombaert:
Attention-based Dynamic Subspace Learners for Medical Image Analysis. CoRR abs/2206.09068 (2022) - 2021
- [j8]Mathilde Bateson, José Dolz, Hoel Kervadec, Hervé Lombaert, Ismail Ben Ayed:
Constrained Domain Adaptation for Image Segmentation. IEEE Trans. Medical Imaging 40(7): 1875-1887 (2021) - [i17]Mathilde Bateson, Jose Dolz, Hoel Kervadec, Hervé Lombaert, Ismail Ben Ayed:
Source-Free Domain Adaptation for Image Segmentation. CoRR abs/2108.03152 (2021) - 2020
- [c33]Mathilde Bateson, Hoel Kervadec, Jose Dolz, Hervé Lombaert, Ismail Ben Ayed:
Source-Relaxed Domain Adaptation for Image Segmentation. MICCAI (1) 2020: 490-499 - [c32]Adrian Galdran, Jose Dolz, Hadi Chakor, Hervé Lombaert, Ismail Ben Ayed:
Cost-Sensitive Regularization for Diabetic Retinopathy Grading from Eye Fundus Images. MICCAI (5) 2020: 665-674 - [i12]Sukesh Adiga V, Jose Dolz, Herve Lombaert:
Manifold-driven Attention Maps for Weakly Supervised Segmentation. CoRR abs/2004.03046 (2020) - [i11]Mathilde Bateson, Hoel Kervadec, Jose Dolz, Herve Lombaert, Ismail Ben Ayed:
Source-Relaxed Domain Adaptation for Image Segmentation. CoRR abs/2005.03697 (2020) - [i9]Adrian Galdran, André Anjos, José Dolz, Hadi Chakor, Hervé Lombaert, Ismail Ben Ayed:
The Little W-Net That Could: State-of-the-Art Retinal Vessel Segmentation with Minimalistic Models. CoRR abs/2009.01907 (2020) - [i7]Adrian Galdran, José Dolz, Hadi Chakor, Hervé Lombaert, Ismail Ben Ayed:
Cost-Sensitive Regularization for Diabetic Retinopathy Grading from Eye Fundus Images. CoRR abs/2010.00291 (2020) - 2019
- [j6]Jose Dolz, Karthik Gopinath, Jing Yuan, Herve Lombaert, Christian Desrosiers, Ismail Ben Ayed:
HyperDense-Net: A Hyper-Densely Connected CNN for Multi-Modal Image Segmentation. IEEE Trans. Medical Imaging 38(5): 1116-1126 (2019) - [c30]Mathilde Bateson, Hoel Kervadec, Jose Dolz, Hervé Lombaert, Ismail Ben Ayed:
Constrained Domain Adaptation for Segmentation. MICCAI (2) 2019: 326-334 - [i6]Mathilde Bateson, Jose Dolz, Hoel Kervadec, Hervé Lombaert, Ismail Ben Ayed:
Constrained domain adaptation for segmentation. CoRR abs/1908.02996 (2019) - 2018
- [i1]Jose Dolz, Karthik Gopinath, Jing Yuan, Herve Lombaert, Christian Desrosiers, Ismail Ben Ayed:
HyperDense-Net: A hyper-densely connected CNN for multi-modal image segmentation. CoRR abs/1804.02967 (2018)
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