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Lucas Drumetz
Lucas Drumetz
IMT Atlantique, Lab-STICC, Brest, France
Zweryfikowany adres z imt-atlantique.fr
Tytuł
Cytowane przez
Cytowane przez
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Blind hyperspectral unmixing using an extended linear mixing model to address spectral variability
L Drumetz, MA Veganzones, S Henrot, R Phlypo, J Chanussot, C Jutten
IEEE Transactions on Image Processing 25 (8), 3890-3905, 2016
2642016
Spectral variability in hyperspectral data unmixing: A comprehensive review
RA Borsoi, T Imbiriba, JCM Bermudez, C Richard, J Chanussot, ...
IEEE geoscience and remote sensing magazine 9 (4), 223-270, 2021
2092021
A new extended linear mixing model to address spectral variability
MA Veganzones, L Drumetz, G Tochon, M Dalla Mura, A Plaza, ...
2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in …, 2014
972014
Hyperspectral image unmixing with endmember bundles and group sparsity inducing mixed norms
L Drumetz, TR Meyer, J Chanussot, AL Bertozzi, C Jutten
IEEE Transactions on Image Processing 28 (7), 3435-3450, 2019
922019
Learning variational data assimilation models and solvers
R Fablet, B Chapron, L Drumetz, E Mémin, O Pannekoucke, F Rousseau
Journal of Advances in Modeling Earth Systems 13 (10), e2021MS002572, 2021
862021
Residual networks as flows of diffeomorphisms
F Rousseau, L Drumetz, R Fablet
Journal of Mathematical Imaging and Vision 62, 365-375, 2020
682020
Learning latent dynamics for partially observed chaotic systems
S Ouala, D Nguyen, L Drumetz, B Chapron, A Pascual, F Collard, ...
Chaos: An Interdisciplinary Journal of Nonlinear Science 30 (10), 2020
592020
Variability of the endmembers in spectral unmixing: Recent advances
L Drumetz, J Chanussot, C Jutten
2016 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in …, 2016
51*2016
Em-like learning chaotic dynamics from noisy and partial observations
D Nguyen, S Ouala, L Drumetz, R Fablet
arXiv preprint arXiv:1903.10335, 2019
472019
Spherical sliced-wasserstein
C Bonet, P Berg, N Courty, F Septier, L Drumetz, MT Pham
Twelfth International Conference on Learning Representations, 2022
452022
Spectral variability aware blind hyperspectral image unmixing based on convex geometry
L Drumetz, J Chanussot, C Jutten, WK Ma, A Iwasaki
IEEE Transactions on Image Processing 29, 4568-4582, 2020
442020
Efficient gradient flows in sliced-Wasserstein space
C Bonet, N Courty, F Septier, L Drumetz
arXiv preprint arXiv:2110.10972, 2021
42*2021
Hyperspectral classification through unmixing abundance maps addressing spectral variability
E Ibarrola-Ulzurrun, L Drumetz, J Marcello, C Gonzalo-Martín, ...
IEEE Transactions on Geoscience and Remote Sensing 57 (7), 4775-4788, 2019
412019
Blind hyperspectral unmixing based on graph total variation regularization
J Qin, H Lee, JT Chi, L Drumetz, J Chanussot, Y Lou, AL Bertozzi
IEEE Transactions on Geoscience and Remote Sensing 59 (4), 3338-3351, 2020
392020
Spectral unmixing: A derivation of the extended linear mixing model from the Hapke model
L Drumetz, J Chanussot, C Jutten
IEEE Geoscience and Remote Sensing Letters 17 (11), 1866-1870, 2019
312019
Joint interpolation and representation learning for irregularly sampled satellite-derived geophysical fields
R Fablet, M Beauchamp, L Drumetz, F Rousseau
Frontiers in Applied Mathematics and Statistics 7, 655224, 2021
242021
Sliced-Wasserstein on symmetric positive definite matrices for M/EEG signals
C Bonet, B Malézieux, A Rakotomamonjy, L Drumetz, T Moreau, ...
International Conference on Machine Learning, 2777-2805, 2023
232023
Joint learning of variational representations and solvers for inverse problems with partially-observed data
R Fablet, L Drumetz, F Rousseau
arXiv preprint arXiv:2006.03653, 2020
232020
Hyperspectral unmixing with material variability using social sparsity
TR Meyer, L Drumetz, J Chanussot, AL Bertozzi, C Jutten
2016 IEEE International Conference on Image Processing (ICIP), 2187-2191, 2016
202016
Preventing manifold intrusion with locality: Local mixup
R Baena, L Drumetz, V Gripon
arXiv preprint arXiv:2201.04368, 2022
182022
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