Profil

Mormont Romain

See author's contact details
ORCID
0000-0002-8117-8913
Main Referenced Co-authors
Marée, Raphaël  (5)
Geurts, Pierre  (3)
Ball, Graeme (1)
Begon, Jean-Michel  (1)
Bäcker, Volker (1)
Main Referenced Keywords
digital pathology (3); transfer learning (3); deep learning (2); machine learning (2); multi-task learning (2);
Main Referenced Unit & Research Centers
Montefiore Institute - Montefiore Institute of Electrical Engineering and Computer Science - ULiège [BE] (2)
Main Referenced Disciplines
Computer science (5)
Electrical & electronics engineering (1)

Publications (total 6)

The most downloaded
1182 downloads
Mormont, R., Geurts, P., & Marée, R. (2018). Comparison of deep transfer learning strategies for digital pathology. In 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE. https://hdl.handle.net/2268/222511

The most cited

87 citations (Scopus®)

Mormont, R., Geurts, P., & Marée, R. (2018). Comparison of deep transfer learning strategies for digital pathology. In 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE. https://hdl.handle.net/2268/222511

Mormont, R., Testouri, M., Marée, R., & Geurts, P. (2022). Relieving pixel-wise labeling effort for pathology image segmentation with self-training. In Lecture Notes in Computer Science. Genève, Switzerland: Springer Cham. doi:10.1007/978-3-031-25082-8_39
Peer reviewed

Mormont, R. (2022). Addressing data scarcity with deep transfer learning and self-training in digital pathology [Doctoral thesis, ULiège - Université de Liège]. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/293358

Rubens, U.* , Mormont, R.* , Paavolainen, L., Bäcker, V., Pavie, B., Scholz, L. A., Michiels, G., Maska, M., Ünay, D., Ball, G., Hoyoux, R., Vandaele, R., Golani, O., Stanciu, S. G., Sladoje, N., Paul-Gilloteaux, P., Marée, R.* , & Tosi, S.*. (12 June 2020). BIAFLOWS: A Collaborative Framework to Reproducibly Deploy and Benchmark Bioimage Analysis Workflows. Patterns, 1. doi:10.1016/j.patter.2020.100040
Peer reviewed
* These authors have contributed equally to this work.

Mormont, R., Geurts, P., & Marée, R. (2020). Multi-task pre-training of deep neural networks for digital pathology. IEEE Journal of Biomedical and Health Informatics. doi:10.1109/JBHI.2020.2992878
Peer Reviewed verified by ORBi

Mormont, R., Geurts, P., & Marée, R. (2018). Comparison of deep transfer learning strategies for digital pathology. In 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE.
Peer reviewed

Mormont, R., Begon, J.-M., Hoyoux, R., & Marée, R. (12 September 2016). SLDC: an open-source workflow for object detection in multi-gigapixel images [Paper presentation]. The 25th Belgian-Dutch Conference on Machine Learning (Benelearn), Kortrijk, Belgium.

Contact ORBi