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2020 – today
- 2022
[b1]Romain Mormont:
Addressing data scarcity with deep transfer learning and self-training in digital pathology. University of Liège, Belgium, 2022- [c2]Romain Mormont
, Mehdi Testouri, Raphaël Marée, Pierre Geurts:
Relieving Pixel-Wise Labeling Effort for Pathology Image Segmentation with Self-training. ECCV Workshops (7) 2022: 577-592 - 2021
- [j2]Romain Mormont, Pierre Geurts, Raphaël Marée:
Multi-Task Pre-Training of Deep Neural Networks for Digital Pathology. IEEE J. Biomed. Health Informatics 25(2): 412-421 (2021) - 2020
- [j1]Ulysse Rubens, Romain Mormont, Lassi Paavolainen, Volker Bäcker, Benjamin Pavie, Leandro A. Scholz, Gino Michiels, Martin Maska, Devrim Ünay, Graeme Ball, Renaud Hoyoux, Rémy Vandaele, Ofra Golani, Stefan G. Stanciu, Natasa Sladoje, Perrine Paul-Gilloteaux, Raphaël Marée, Sébastien Tosi:
BIAFLOWS: A Collaborative Framework to Reproducibly Deploy and Benchmark Bioimage Analysis Workflows. Patterns 1(3): 100040 (2020) - [i1]Romain Mormont, Pierre Geurts, Raphaël Marée:
Multi-task pre-training of deep neural networks for digital pathology. CoRR abs/2005.02561 (2020)
2010 – 2019
- 2018
- [c1]Romain Mormont, Pierre Geurts, Raphaël Marée:
Comparison of Deep Transfer Learning Strategies for Digital Pathology. CVPR Workshops 2018: 2262-2271
Coauthor Index
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