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Hannah Dröge
Hannah Dröge
Verified email at uni-bonn.de - Homepage
Title
Cited by
Cited by
Year
Inverting gradients-how easy is it to break privacy in federated learning?
J Geiping, H Bauermeister, H Dröge, M Moeller
Advances in neural information processing systems 33, 16937-16947, 2020
13172020
Mitral valve segmentation using robust nonnegative matrix factorization
H Dröge, B Yuan, R Llerena, JT Yen, M Moeller, AL Bertozzi
Journal of Imaging 7 (10), 213, 2021
62021
Evaluating Adversarial Robustness of Low dose CT Recovery
K Vaishnavi Gandikota, P Chandramouli, H Droege, M Moeller
arXiv e-prints, arXiv: 2402.11557, 2024
4*2024
Explorable Data Consistent CT Reconstruction.
H Dröge, Y Bahat, F Heide, M Möller
BMVC, 746, 2022
32022
Learning or modelling? an analysis of single image segmentation based on scribble information
H Dröge, M Moeller
2021 IEEE International Conference on Image Processing (ICIP), 2274-2278, 2021
32021
Kissing to find a match: efficient low-rank permutation representation
H Dröge, Z Lähner, Y Bahat, O Martorell Nadal, F Heide, M Möller
Advances in Neural Information Processing Systems 36, 2024
22024
Non-Smooth Energy Dissipating Networks
H Dröge, T Möllenhoff, M Möller
2022 IEEE International Conference on Image Processing (ICIP), 3281-3285, 2022
22022
VHS: High-Resolution Iterative Stereo Matching with Visual Hull Priors
M Plack, H Dröge, L Van Holland, MB Hullin
arXiv preprint arXiv:2406.02552, 2024
2024
On the confluence of machine learning and model-based energy minimization methods for computer vision
H Dröge
2024
Robustness and exploration of variational and machine learning approaches to inverse problems: An overview
A Auras, KV Gandikota, H Droege, M Moeller
GAMM‐Mitteilungen, e202470003, 2024
2024
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Articles 1–10