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Lucas Drumetz
Lucas Drumetz
IMT Atlantique, Lab-STICC, Brest, France
Verified email at imt-atlantique.fr
Title
Cited by
Cited by
Year
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
2352016
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
1602021
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
922014
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
842019
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
622021
Residual networks as flows of diffeomorphisms
F Rousseau, L Drumetz, R Fablet
Journal of Mathematical Imaging and Vision 62, 365-375, 2020
592020
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
522020
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
402019
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
382019
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
342020
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
332019
Spherical sliced-wasserstein
C Bonet, P Berg, N Courty, F Septier, L Drumetz, MT Pham
Twelfth International Conference on Learning Representations, 2022
302022
Efficient gradient flows in sliced-Wasserstein space
C Bonet, N Courty, F Septier, L Drumetz
arXiv preprint arXiv:2110.10972, 2021
27*2021
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
252020
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
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
192021
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
162020
Preventing manifold intrusion with locality: Local mixup
R Baena, L Drumetz, V Gripon
arXiv preprint arXiv:2201.04368, 2022
152022
Variational deep learning for the identification and reconstruction of chaotic and stochastic dynamical systems from noisy and partial observations
D Nguyen, S Ouala, L Drumetz, R Fablet
arXiv preprint arXiv:2009.02296, 2020
152020
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Articles 1–20