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Joint and Progressive Subspace Analysis (JPSA) with Spatial-Spectral Manifold Alignment for Semi-Supervised Hyperspectral Dimensionality Reduction

Hong, Danfeng and Yokoya, Naoto and Chanussot, Jocelyn and Xu, Jian and Zhu, Xiao Xiang (2021) Joint and Progressive Subspace Analysis (JPSA) with Spatial-Spectral Manifold Alignment for Semi-Supervised Hyperspectral Dimensionality Reduction. IEEE Transactions on Cybernetics. IEEE - Institute of Electrical and Electronics Engineers. doi: 10.1109/tcyb.2020.3028931. ISSN 2168-2267. (In Press)

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Item URL in elib:https://elib.dlr.de/136188/
Document Type:Article
Title:Joint and Progressive Subspace Analysis (JPSA) with Spatial-Spectral Manifold Alignment for Semi-Supervised Hyperspectral Dimensionality Reduction
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Hong, DanfengDanfeng.Hong (at) dlr.deUNSPECIFIED
Yokoya, NaotoRIKENUNSPECIFIED
Chanussot, JocelynInstitute Nationale Polytechnique de GrenobleUNSPECIFIED
Xu, Jianjian.xu (at) dlr.dehttps://orcid.org/0000-0003-2348-125X
Zhu, Xiao Xiangxiao.zhu (at) dlr.deUNSPECIFIED
Date:2021
Journal or Publication Title:IEEE Transactions on Cybernetics
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
DOI :10.1109/tcyb.2020.3028931
Publisher:IEEE - Institute of Electrical and Electronics Engineers
ISSN:2168-2267
Status:In Press
Keywords:Dimensionality reduction, hyperspectral data, joint learning, manifold alignment, progressive learning, spatialspectral, semi-supervised, subspace learning.
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Optical remote sensing, R - Vorhaben hochauflösende Fernerkundungsverfahren (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > EO Data Science
Deposited By: Liu, Rong
Deposited On:26 Nov 2020 11:11
Last Modified:14 Jan 2021 13:32

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