Learnable manifold alignment (LeMA): A semi-supervised cross-modality learning framework for land cover and land use classification

Danfeng Hong (1) , Naoto Yokoya (2) , Nan Ge (1) , Jocelyn Chanussot (3) , Xiao Xiang Zhu (4, 5)

1 IMF - DLR Institut für Methodik der Fernerkundung / DLR Remote Sensing Technology Institute
2 UTokyo - The University of Tokyo
3 GIPSA-SIGMAPHY - GIPSA - Signal Images Physique
4 DLR - German Aerospace Center
5 TUM - Technische Universität Munchen - Technical University Munich - Université Technique de Munich

Domaines: Traitement du signal et de l'image [eess.SP]

Danfeng Hong, Naoto Yokoya, Nan Ge, Jocelyn Chanussot, Xiao Xiang Zhu. Learnable manifold alignment (LeMA): A semi-supervised cross-modality learning framework for land cover and land use classification. ISPRS Journal of Photogrammetry and Remote Sensing, 2019, ISPRS Journal of Photogrammetry and Remote Sensing,2019, 147, pp.193-205. ⟨10.1016/j.isprsjprs.2018.10.006⟩. ⟨hal-01961357⟩