Watch the Dallas Symposium LIVE, and fundraiser auction
Ticket proceeds support mindat.org! - click here...
Log InRegister
Quick Links : The Mindat ManualThe Rock H. Currier Digital LibraryMindat Newsletter [Free Download]
Home PageAbout MindatThe Mindat ManualHistory of MindatCopyright StatusWho We AreContact UsAdvertise on Mindat
Donate to MindatCorporate SponsorshipSponsor a PageSponsored PagesMindat AdvertisersAdvertise on Mindat
Learning CenterWhat is a mineral?The most common minerals on earthInformation for EducatorsMindat ArticlesThe ElementsThe Rock H. Currier Digital LibraryGeologic Time
Minerals by PropertiesMinerals by ChemistryAdvanced Locality SearchRandom MineralRandom LocalitySearch by minIDLocalities Near MeSearch ArticlesSearch GlossaryMore Search Options
Search For:
Mineral Name:
Locality Name:
Keyword(s):
 
The Mindat ManualAdd a New PhotoRate PhotosLocality Edit ReportCoordinate Completion ReportAdd Glossary Item
Mining CompaniesStatisticsUsersMineral MuseumsClubs & OrganizationsMineral Shows & EventsThe Mindat DirectoryDevice SettingsThe Mineral Quiz
Photo SearchPhoto GalleriesSearch by ColorNew Photos TodayNew Photos YesterdayMembers' Photo GalleriesPast Photo of the Day GalleryPhotography

Deng, Yang-Jun, Li, Heng-Chao, Tan, Si-Qiao, Hou, Junhui, Du, Qian, Plaza, Antonio (2023) t-Linear Tensor Subspace Learning for Robust Feature Extraction of Hyperspectral Images. IEEE Transactions on Geoscience and Remote Sensing, 61. 1-15 doi:10.1109/tgrs.2023.3233945

Advanced
   -   Only viewable:
Reference TypeJournal (article/letter/editorial)
Titlet-Linear Tensor Subspace Learning for Robust Feature Extraction of Hyperspectral Images
JournalIEEE Transactions on Geoscience and Remote Sensing
AuthorsDeng, Yang-JunAuthor
Li, Heng-ChaoAuthor
Tan, Si-QiaoAuthor
Hou, JunhuiAuthor
Du, QianAuthor
Plaza, AntonioAuthor
Year2023Volume61
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
DOIdoi:10.1109/tgrs.2023.3233945Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID15670041Long-form Identifiermindat:1:5:15670041:4
GUID0
Full ReferenceDeng, Yang-Jun, Li, Heng-Chao, Tan, Si-Qiao, Hou, Junhui, Du, Qian, Plaza, Antonio (2023) t-Linear Tensor Subspace Learning for Robust Feature Extraction of Hyperspectral Images. IEEE Transactions on Geoscience and Remote Sensing, 61. 1-15 doi:10.1109/tgrs.2023.3233945
Plain TextDeng, Yang-Jun, Li, Heng-Chao, Tan, Si-Qiao, Hou, Junhui, Du, Qian, Plaza, Antonio (2023) t-Linear Tensor Subspace Learning for Robust Feature Extraction of Hyperspectral Images. IEEE Transactions on Geoscience and Remote Sensing, 61. 1-15 doi:10.1109/tgrs.2023.3233945
In(2023) IEEE Transactions on Geoscience and Remote Sensing Vol. 61. Institute of Electrical and Electronics Engineers (IEEE)

See Also

These are possibly similar items as determined by title/reference text matching only.

Deng, Yang-Jun, Yang, Meng-Long, Li, Heng-Chao, Long, Chen-Feng, Fang, Kui, Du, Qian (2024) Feature Dimensionality Reduction With L2,p-Norm-Based Robust Embedding Regression for Classification of Hyperspectral Images. IEEE Transactions on Geoscience and Remote Sensing, 62. 1-14 doi:10.1109/tgrs.2024.3363159
Deng, Yang-Jun; Zhang, Lv-Wei; Ren, Longfei; Zhu, Xinghui; Li, Heng-Chao; Du, Qian (2025) Tensor Decomposition-Based Relaxed Linear Regression for Hyperspectral Image Classification. IEEE Transactions on Geoscience and Remote Sensing, 63. doi:10.1109/tgrs.2025.3571524
Li, Heng-Chao, Feng, Xin-Ru, Zhai, Dong-Hai, Du, Qian, Plaza, Antonio (2022) Self-Supervised Robust Deep Matrix Factorization for Hyperspectral Unmixing. IEEE Transactions on Geoscience and Remote Sensing, 60. 1-14 doi:10.1109/tgrs.2021.3107151
Lu, Pengyu, Jiang, Xinwei, Zhang, Yongshan, Liu, Xiaobo, Cai, Zhihua, Jiang, Junjun, Plaza, Antonio (2023) Spectral–Spatial and Superpixelwise Unsupervised Linear Discriminant Analysis for Feature Extraction and Classification of Hyperspectral Images. IEEE Transactions on Geoscience and Remote Sensing, 61. 1-15 doi:10.1109/tgrs.2023.3330474
Song, Xin, Li, Heng-Chao, Pan, Lei, Deng, Yang-Jun, Zhang, Pu, You, Li, Du, Qian (2022) Unsupervised Robust Projection Learning by Low-Rank and Sparse Decomposition for Hyperspectral Feature Extraction. IEEE Geoscience and Remote Sensing Letters, 19. 1-5 doi:10.1109/lgrs.2021.3065252
Deng, Yang-Jun, Li, Heng-Chao, Song, Xin, Sun, Yong-Jian, Zhang, Xiang-Rong, Du, Qian (2020) Patch Tensor-Based Multigraph Embedding Framework for Dimensionality Reduction of Hyperspectral Images. IEEE Transactions on Geoscience and Remote Sensing, 58 (3) 1630-1643 doi:10.1109/tgrs.2019.2947200
Deng, Yang-Jun, Li, Heng-Chao, Fu, Kun, Du, Qian, Emery, William J. (2018) Tensor Low-Rank Discriminant Embedding for Hyperspectral Image Dimensionality Reduction. IEEE Transactions on Geoscience and Remote Sensing, 56 (12) 7183-7194 doi:10.1109/tgrs.2018.2849085
Zhang, Shaoquan, Li, Jun, Li, Heng-Chao, Deng, Chengzhi, Plaza, Antonio (2018) Spectral–Spatial Weighted Sparse Regression for Hyperspectral Image Unmixing. IEEE Transactions on Geoscience and Remote Sensing, 56 (6) 3265-3276 doi:10.1109/tgrs.2018.2797200
Deng, Yang-Jun, Li, Heng-Chao, Pan, Lei, Shao, Li-Yang, Du, Qian, Emery, William J. (2018) Modified Tensor Locality Preserving Projection for Dimensionality Reduction of Hyperspectral Images. IEEE Geoscience and Remote Sensing Letters, 15 (2) 277-281 doi:10.1109/lgrs.2017.2786223
Wang, Meng, Gao, Feng, Dong, Junyu, Li, Heng-Chao, Du, Qian (2023) Nearest Neighbor-Based Contrastive Learning for Hyperspectral and LiDAR Data Classification. IEEE Transactions on Geoscience and Remote Sensing, 61. 1-16 doi:10.1109/tgrs.2023.3236154
Liao, Xiaolong, Tu, Bing, Li, Jun, Plaza, Antonio (2023) Class-wise Graph Embedding-Based Active Learning for Hyperspectral Image Classification. IEEE Transactions on Geoscience and Remote Sensing, 61. 1-13 doi:10.1109/tgrs.2023.3309032
 
and/or  
Mindat.org is an outreach project of the Hudson Institute of Mineralogy, a 501(c)(3) not-for-profit organization.
Copyright © mindat.org and the Hudson Institute of Mineralogy 1993-2025, except where stated. Most political location boundaries are © OpenStreetMap contributors. Mindat.org relies on the contributions of thousands of members and supporters. Founded in 2000 by Jolyon Ralph.
To cite: Ralph, J., Von Bargen, D., Martynov, P., Zhang, J., Que, X., Prabhu, A., Morrison, S. M., Li, W., Chen, W., & Ma, X. (2025). Mindat.org: The open access mineralogy database to accelerate data-intensive geoscience research. American Mineralogist, 110(6), 833–844. doi:10.2138/am-2024-9486.
Privacy Policy - Terms & Conditions - Contact Us / DMCA issues - Report a bug/vulnerability Current server date and time: August 21, 2025 16:33:48
Go to top of page