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Stine Hansen
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2020 – today
- 2023
- [j4]Stine Hansen
, Srishti Gautam
ADNet++: A few-shot learning framework for multi-class medical image volume segmentation with uncertainty-guided feature refinement. Medical Image Anal. 89: 102870 (2023) - [j3]Srishti Gautam, Marina M.-C. Höhne, Stine Hansen, Robert Jenssen, Michael Kampffmeyer:
This looks More Like that: Enhancing Self-Explaining Models by Prototypical Relevance Propagation. Pattern Recognit. 136: 109172 (2023) - [c4]Luca Tomasetti, Stine Hansen, Mahdieh Khanmohammadi
Self-Supervised Few-Shot Learning for Ischemic Stroke Lesion Segmentation. ISBI 2023: 1-5 - [i6]Luca Tomasetti, Stine Hansen, Mahdieh Khanmohammadi, Kjersti Engan, Liv Jorunn Høllesli, Kathinka Dæhli Kurz, Michael Kampffmeyer:
Self-Supervised Few-Shot Learning for Ischemic Stroke Lesion Segmentation. CoRR abs/2303.01332 (2023) - [i5]Ribana Roscher, Marc Rußwurm, Caroline Gevaert
Data-Centric Machine Learning for Geospatial Remote Sensing Data. CoRR abs/2312.05327 (2023) - 2022
- [j2]Stine Hansen
Anomaly detection-inspired few-shot medical image segmentation through self-supervision with supervoxels. Medical Image Anal. 78: 102385 (2022) - [c3]Suaiba Amina Salahuddin, Stine Hansen, Srishti Gautam, Michael Kampffmeyer, Robert Jenssen:
A self-guided anomaly detection-inspired few-shot segmentation network. CVCS 2022 - [c2]Srishti Gautam, Marina M.-C. Höhne, Stine Hansen, Robert Jenssen, Michael Kampffmeyer:
Demonstrating the Risk of Imbalanced Datasets in Chest X-Ray Image-Based Diagnostics by Prototypical Relevance Propagation. ISBI 2022: 1-5 - [c1]Srishti Gautam, Ahcène Boubekki, Stine Hansen, Suaiba Amina Salahuddin, Robert Jenssen, Marina M.-C. Höhne, Michael Kampffmeyer:
ProtoVAE: A Trustworthy Self-Explainable Prototypical Variational Model. NeurIPS 2022 - [i4]Srishti Gautam, Marina M.-C. Höhne, Stine Hansen, Robert Jenssen, Michael Kampffmeyer:
Demonstrating The Risk of Imbalanced Datasets in Chest X-ray Image-based Diagnostics by Prototypical Relevance Propagation. CoRR abs/2201.03559 (2022) - [i3]Stine Hansen, Srishti Gautam, Robert Jenssen, Michael Kampffmeyer:
Anomaly Detection-Inspired Few-Shot Medical Image Segmentation Through Self-Supervision With Supervoxels. CoRR abs/2203.02048 (2022) - [i2]Srishti Gautam, Ahcene Boubekki
ProtoVAE: A Trustworthy Self-Explainable Prototypical Variational Model. CoRR abs/2210.08151 (2022) - 2021
- [j1]Stine Hansen
Unsupervised supervoxel-based lung tumor segmentation across patient scans in hybrid PET/MRI. Expert Syst. Appl. 167: 114244 (2021) - [i1]Srishti Gautam, Marina M.-C. Höhne, Stine Hansen, Robert Jenssen, Michael Kampffmeyer:
This looks more like that: Enhancing Self-Explaining Models by Prototypical Relevance Propagation. CoRR abs/2108.12204 (2021)
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