These publications have been fully or partially funded by ASTRAL project.
To have a full research on HAL : search_ASTRAL
The codes associated to some of the publications are available here : RING
2022
Conferences
Self-supervised training strategies for SAR image despeckling with deep neural networks Emanuele Dalsasso, Loïc Denis, Max Muzeau, Florence Tupin 14th European Conference on Synthetic Aperture Radar (EUSAR), Jul 2022, Leipzig, Germany
2023
Journal papers
Multi-temporal speckle reduction with self-supervised deep neural networks, Inès Meraoumia, Emanuele Dalsasso, Loïc Denis, Rémy Abergel, Florence Tupin IEEE Transactions on Geoscience and Remote Sensing, 2023
A Deep Learning Approach for SAR Tomographic Imaging of Forested Areas Zoé Berenger, Loïc Denis, Florence Tupin, Laurent Ferro-Famil, Yue Huang IEEE Geoscience and Remote Sensing Letters, In press
MERLIN-Seg: self-supervised despeckling for label-efficient semantic segmentation, E. Dalsasso, C. Rambour, F. Brigui, N. Thome (soumis à Computer Vision and Image Understanding CVIU) , 2023
Robustness to spatially correlated speckle in Plug and Play polSAR depseckling, C. Ulondu Mendes, L. Denis, C. Deladalle, F. Tupin (soumis à IEEE Transactions on Geoscience and Remote Sensing), 2023
Conferences
Débruitage multi-modal d’images radar à synthèse d’ouverture par apprentissage profond auto-supervisé Victor Gaya, Emanuele Dalsasso, Loïc Denis, Florence Tupin, Béatrice Pinel-Puysségur, Cyrielle Guérin GRETSI, Aug 2023, Grenoble, France
APPLYING DEEP LEARNING TO P-BAND SAR TOMOGRAPHIC IMAGING IN PREPARATION FOR THE FUTURE BIOMASS MISSION Zoé Berenger, Loïc Denis, Florence Tupin, Laurent Ferro-Famil IGARSS, Jul 2023, Pasadena, United States
