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

In this paper, we aim at tackling a general but interesting cross-modality feature learning question in remote sensing community—can a limited amount of highly-discriminative (e.g., hyperspectral) training data improve the performance of a classification task using a large amount of poorly-discrimin...

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Detalles Bibliográficos
Publicado en:ISPRS J Photogramm Remote Sens
Main Authors: Hong, Danfeng, Yokoya, Naoto, Ge, Nan, Chanussot, Jocelyn, Zhu, Xiao Xiang
Formato: Artigo
Idioma:Inglês
Publicado: Elsevier 2019
Assuntos:
Acceso en liña:https://ncbi.nlm.nih.gov/pmc/articles/PMC6360532/
https://ncbi.nlm.nih.gov/pubmed/30774220
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.isprsjprs.2018.10.006
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