188 citations · 762 across the 33 of their papers we have counts for
5 papers · 1 filter
Reduction of rain-induced errors for wind speed estimation on SAR observations using convolutional neural networks
Aurélien Colin, Pierre Tandeo, Charles Peureux +2
Synthetic Aperture Radar is known to be able to provide high-resolution estimates of surface wind speed. These estimates usually rely on a Geophysical Model Function (GMF) that has…
Multimodal learning-based inversion models for the space-time reconstruction of satellite-derived geophysical fields
Ronan Fablet, Bertrand Chapron
For numerous earth observation applications, one may benefit from various satellite sensors to address the reconstruction of some process or information of interest. A variety of s…
End-to-end learning of energy-based representations for irregularly-sampled signals and images
Ronan Fablet, Lucas Drumetz, François Rousseau
For numerous domains, including for instance earth observation, medical imaging, astrophysics,..., available image and signal datasets often involve irregular space-time sampling p…
Residual Networks as Geodesic Flows of Diffeomorphisms
Francois Rousseau, Ronan Fablet
This paper addresses the understanding and characterization of residual networks (ResNet), which are among the state-of-the-art deep learning architectures for a variety of supervi…
EddyNet: A Deep Neural Network For Pixel-Wise Classification of Oceanic Eddies
Redouane Lguensat, Miao Sun, Ronan Fablet +3
This work presents EddyNet, a deep learning based architecture for automated eddy detection and classification from Sea Surface Height (SSH) maps provided by the Copernicus Marine…