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Domain adaptation in remote sensing through cross-image synthesis with dictionaries.

, , , and . IGARSS, page 3714-3717. IEEE, (2014)

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Domain adaptation in remote sensing through cross-image synthesis with dictionaries., , , and . IGARSS, page 3714-3717. IEEE, (2014)Kernel Low-Rank and Sparse Graph for Unsupervised and Semi-Supervised Classification of Hyperspectral Images., , , , and . IEEE Trans. Geosci. Remote. Sens., 54 (6): 3410-3420 (2016)Multi-sensor change detection based on nonlinear canonical correlations., , , , and . IGARSS, page 1944-1947. IEEE, (2013)Cluster validity measure and merging system for hierarchical clustering considering outliers., , , , and . Pattern Recognit., 48 (4): 1478-1489 (2015)Estimation of soil moisture from airborne hyperspectral imagery with support vector regression., , , , and . WHISPERS, page 1-4. IEEE, (2013)Multisource clustering of remote sensing images with Entropy-based Dempster-Shafer fusion., , , , , , and . EUSIPCO, page 1-5. IEEE, (2013)Non-linear low-rank and sparse representation for hyperspectral image analysis., , , , and . IGARSS, page 4648-4651. IEEE, (2014)Semi-Supervised Novelty Detection Using SVM Entire Solution Path., , , , and . IEEE Trans. Geosci. Remote. Sens., 51 (4-1): 1939-1950 (2013)Semi-supervised and unsupervised novelty detection using nested support vector machines., , , , and . IGARSS, page 7337-7340. IEEE, (2012)Hierarchical sparse representation for dictionary-based classification of hyperspectral images., , , , and . WHISPERS, page 1-4. IEEE, (2014)