Guided deep decoder: Unsupervised image pair fusion T Uezato, D Hong, N Yokoya, W He European Conference on Computer Vision, 87-102, 2020 | 89 | 2020 |
Hyperspectral unmixing with spectral variability using adaptive bundles and double sparsity T Uezato, M Fauvel, N Dobigeon IEEE Transactions on Geoscience and Remote Sensing 57 (6), 3980-3992, 2019 | 48 | 2019 |
A novel endmember bundle extraction and clustering approach for capturing spectral variability within endmember classes T Uezato, RJ Murphy, A Melkumyan, A Chlingaryan IEEE Transactions on Geoscience and Remote Sensing 54 (11), 6712-6731, 2016 | 43 | 2016 |
Hyperspectral image unmixing with LiDAR data-aided spatial regularization T Uezato, M Fauvel, N Dobigeon IEEE Transactions on Geoscience and Remote Sensing 56 (7), 4098-4108, 2018 | 39 | 2018 |
A novel spectral unmixing method incorporating spectral variability within endmember classes T Uezato, RJ Murphy, A Melkumyan, A Chlingaryan IEEE Transactions on Geoscience and Remote Sensing 54 (5), 2812-2831, 2015 | 38 | 2015 |
Mineralogical mapping of southern Namibia by application of continuum-removal MSAM method to the HyMap data S Oshigami, Y Yamaguchi, T Uezato, A Momose, Y Arvelyna, Y Kawakami, ... International journal of remote sensing 34 (15), 5282-5295, 2013 | 31 | 2013 |
Incorporating spatial information and endmember variability into unmixing analyses to improve abundance estimates T Uezato, RJ Murphy, A Melkumyan, A Chlingaryan IEEE Transactions on Image Processing 25 (12), 5563-5575, 2016 | 24 | 2016 |
Illumination invariant hyperspectral image unmixing based on a digital surface model T Uezato, N Yokoya, W He IEEE Transactions on Image Processing 29, 3652-3664, 2020 | 20 | 2020 |
Learning mutual modulation for self-supervised cross-modal super-resolution X Dong, N Yokoya, L Wang, T Uezato European Conference on Computer Vision, 1-18, 2022 | 18 | 2022 |
Spectrum-aware and transferable architecture search for hyperspectral image restoration W He, Q Yao, N Yokoya, T Uezato, H Zhang, L Zhang European Conference on Computer Vision, 19-37, 2022 | 12 | 2022 |
Hierarchical sparse nonnegative matrix factorization for hyperspectral unmixing with spectral variability T Uezato, M Fauvel, N Dobigeon Remote Sensing 12 (14), 2326, 2020 | 8 | 2020 |
Multiple endmember spectral unmixing within a multi-task framework T Uezato, RJ Murphy, A Melkumyan, A Chlingaryan, S Schneider 2014 IEEE Geoscience and Remote Sensing Symposium, 3454-3457, 2014 | 6 | 2014 |
Multisource Remote Sensing Image Fusion W He, D Hong, G Scarpa, T Uezato, N Yokoya Deep Learning for the Earth Sciences: A Comprehensive Approach to Remote …, 2021 | 3 | 2021 |
Interpretable deep attention prior for image restoration and enhancement W He, T Uezato, N Yokoya IEEE Transactions on Computational Imaging 9, 185-196, 2023 | 2 | 2023 |
LiDAR-Guided Reduction Of Spectral Variability in Hyperspectral Imagery S Kahraman, R Bacher, T Uezato, J Chanussot, A Tangel 2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution …, 2019 | 2 | 2019 |
A multiple endmember mixing model to handle spectral variability in hyperspectral unmixing T Uezato, M Fauvel, N Dobigeon 2018 9th Workshop on Hyperspectral Image and Signal Processing: Evolution in …, 2018 | 2 | 2018 |
LiDAR-driven spatial regularization for hyperspectral unmixing T Uezat, M Fauvel, N Dobigeon IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium …, 2018 | 2 | 2018 |
Spectral curve-based endmember extraction method T Uezato, RJ Murphy, A Melkumyan, A Chlingaryan 2015 7th Workshop on Hyperspectral Image and Signal Processing: Evolution in …, 2015 | 1 | 2015 |
Multisource Remote Sensing Image Fusion H Wei, D Hong, G Scarpa, T Uezato, N Yokoya Deep Learning for the Earth Sciences, 136-149, 2021 | | 2021 |
Prédiction des services écosystémiques dans les paysages agricoles par télédétection hyperspectrale M Fauvel, R Duflot, T Uezato, N Dobigeon, A Vialatte, D Sheeren, ... 6. Colloque de la Société Française de Photogrammétrie et Télédétection …, 2018 | | 2018 |