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ORCIDFrançois Rousseau 0002
Publications
- 2022
[c52]Simon Benaïchouche, C. Le Goff, Brahim Boussidi, François Rousseau
, Ronan Fablet:
Learnable Variational Models for the Reconstruction of Sea Surface Currents Using Ais Data Streams: A Case Study on the Sicily Channel. IGARSS 2022: 6821-6824- 2021
- [j29]Ronan Fablet, Maxime Beauchamp, Lucas Drumetz, François Rousseau:
Joint Interpolation and Representation Learning for Irregularly Sampled Satellite-Derived Geophysical Fields. Frontiers Appl. Math. Stat. 7: 655224 (2021) - [j27]Simon Benaïchouche, Clément Le Goff, Yann Guichoux, François Rousseau, Ronan Fablet:
Unsupervised Reconstruction of Sea Surface Currents from AIS Maritime Traffic Data Using Trainable Variational Models. Remote. Sens. 13(16): 3162 (2021) - [c51]Ronan Fablet, Lucas Drumetz, François Rousseau:
End-to-End Learning of Variational Models and Solvers for the Resolution of Interpolation Problems. ICASSP 2021: 2360-2364 - [c50]Simon Benaïchouche, Clément Le Goff, Yann Guichoux, François Rousseau, Ronan Fablet:
Unsupervised Reconstruction of Sea Surface Currents from AIS Maritime Traffic Data Using Learnable Variational Models. ICASSP 2021: 4100-4104 - 2020
- [j26]Quentin Delannoy, Chi-Hieu Pham, Clément Cazorla, Carlos Tor-Díez, Guillaume Dollé, Hélène Meunier, Nathalie Bednarek, Ronan Fablet, Nicolas Passat, François Rousseau:
SegSRGAN: Super-resolution and segmentation using generative adversarial networks - Application to neonatal brain MRI. Comput. Biol. Medicine 120: 103755 (2020) - [j25]François Rousseau, Lucas Drumetz, Ronan Fablet:
Residual Networks as Flows of Diffeomorphisms. J. Math. Imaging Vis. 62(3): 365-375 (2020) - [i5]Ronan Fablet, Lucas Drumetz, François Rousseau:
Joint learning of variational representations and solvers for inverse problems with partially-observed data. CoRR abs/2006.03653 (2020) - [i4]Ronan Fablet, Bertrand Chapron, Lucas Drumetz, Étienne Mémin, Olivier Pannekoucke, François Rousseau:
Learning Variational Data Assimilation Models and Solvers. CoRR abs/2007.12941 (2020) - 2019
- [j24]Chi-Hieu Pham, Carlos Tor-Díez, Hélène Meunier, Nathalie Bednarek, Ronan Fablet, Nicolas Passat, François Rousseau:
Multiscale brain MRI super-resolution using deep 3D convolutional networks. Comput. Medical Imaging Graph. 77 (2019) - [c44]Ronan Fablet, Julien Le Sommer, J. M. Molines, Lucas Drumetz, François Rousseau, Bertrand Chapron:
Learning Differential Transport Operators for the Joint Super-Resolution of Sea Surface Tracers and Prediction of Subgrid-Scale Features. IGARSS 2019: 7916-7919 - [c43]Chi-Hieu Pham, Carlos Tor-Díez, Hélène Meunier, Nathalie Bednarek, Ronan Fablet, Nicolas Passat, François Rousseau:
Simultaneous Super-Resolution and Segmentation Using a Generative Adversarial Network: Application to Neonatal Brain MRI. ISBI 2019: 991-994 - [i2]Ronan Fablet, Lucas Drumetz, François Rousseau:
End-to-end learning of energy-based representations for irregularly-sampled signals and images. CoRR abs/1910.00556 (2019) - 2018
- [i1]François Rousseau, Ronan Fablet:
Residual Networks as Geodesic Flows of Diffeomorphisms. CoRR abs/1805.09585 (2018) - 2017
- [c37]Chi-Hieu Pham, Aurélien Ducournau, Ronan Fablet, François Rousseau:
Brain MRI super-resolution using deep 3D convolutional networks. ISBI 2017: 197-200 - 2016
- [j18]Ronan Fablet, François Rousseau:
Joint Interpolation of Multisensor Sea Surface Temperature Fields Using Nonlocal and Statistical Priors. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 9(6): 2665-2675 (2016) - [c35]Luis Tobias, Aurélien Ducournau, François Rousseau, Grégoire Mercier, Ronan Fablet:
Convolutional Neural Networks for object recognition on mobile devices: A case study. ICPR 2016: 3530-3535 - 2015
- [c33]Ronan Fablet, François Rousseau:
Missing data super-resolution using non-local and statistical priors. ICIP 2015: 676-680 - 2003
- [c3]François Rousseau, Ronan Fablet, Christian Barillot:
Robust statistical registration of 3D ultrasound images using texture information. ICIP (1) 2003: 581-584
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