| Neural network approaches to reconstruct phytoplankton time-series in the global ocean E Martinez, A Brini, T Gorgues, L Drumetz, J Roussillon, P Tandeo, ... Remote Sensing 12 (24), 4156, 2020 | 15 | 2020 |
| A Multi-Mode Convolutional Neural Network to reconstruct satellite-derived chlorophyll-a time series in the global ocean from physical drivers J Roussillon, R Fablet, T Gorgues, L Drumetz, J Littaye, E Martinez Frontiers in Marine Science 10, 1077623, 2023 | 12 | 2023 |
| Développement de méthodes innovantes de cartographie de l’occupation du sol à partir de séries temporelles d’images haute résolution visible (NDVI) J Roussillon Mémoire présenté en vue d’obtenir le diplôme d’ingénieur cnam, 2016 | 6 | 2016 |
| Contrasted Trends in Chlorophyll‐a Satellite Products E Pauthenet, E Martinez, T Gorgues, J Roussillon, L Drumetz, R Fablet, ... Geophysical Research Letters 51 (14), e2024GL108916, 2024 | 1 | 2024 |
| Chlorophyll-a satellite climate time series: How machine learning can help distinguish between bias and consistency E Pauthenet, E Martinez, T Gorgues, J Roussillon, L Drumetz, R Fablet, ... EGU24, 2024 | | 2024 |
| Contrasted trends in satellite derived ocean color time-series & potential benefits from machine learning EC Martinez, E Pauthenet, T Gorgues, J Roussillon, R Fablet, L Drumetz, ... 2024 Ocean Sciences Meeting, 2024 | | 2024 |
| Assessing the relative importance of atmospheric dust deposition vs. ocean dynamic in shaping global phytoplankton distribution: a deep learning approach J Roussillon, T Gorgues, EC Martinez, L Drumetz, R Fablet 2024 Ocean Sciences Meeting, 2024 | | 2024 |
| Correction: Martinez et al. Neural Network Approaches to Reconstruct Phytoplankton Time-Series in the Global Ocean. Remote Sens. 2020, 12, 4156 E Martinez, A Brini, T Gorgues, L Drumetz, J Roussillon, P Tandeo, ... Remote Sensing 14 (22), 5669, 2022 | | 2022 |
| Spatial multi-modality as a way to improve both performance and interpretability of deep learning models to reconstruct phytoplankton time-series in the global ocean J Roussillon, J Littaye, R Fablet, L Drumetz, T Gorgues, E Martinez EGU General Assembly Conference Abstracts, EGU22-4534, 2022 | | 2022 |
| Deep learning approach to reconstruct satellite ocean color time series in the global ocean J Roussillon, R Fablet, L Drumetz, T Gorgues, E Martinez EGU General Assembly Conference Abstracts, EGU21-11974, 2021 | | 2021 |
| Wind erosion and dust emission in the Sahel: a regional modelling approach to evaluate the impact of climate and land-use A Touré, B Marticorena, G Siour, C Pierre, C Bouet, G Bergametti, ... les 30 ans d'Amma-Catch, 2018 | | 2018 |
| Impact of land use on wind erosion and dust emission in the Sahel: a regional modelling approach B Marticorena, G Siour, C Pierre, C Bouet, G Bergametti, ... INTERNATIONAL CONFERENCE ON AEOLIAN RESEARCH 2018, 2018 | | 2018 |
| Impact of land use on wind erosion and dust emission in the Sahel: a regional modelling approach F Couvreux, F Guichard, M Grippa, P Hiernaux, L Kergoat, Y Largeron, ... | | |