- Author
- Shaoguang Huang (UGent) , Hongyan Zhang and Aleksandra Pizurica (UGent)
- Organization
- Keywords
- REMOTE-SENSING IMAGES, MORPHOLOGICAL PROFILES, VECTOR MACHINES, RECOVERY, PURSUIT, SUPPORT, FUSION
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-8537836
- MLA
- Huang, Shaoguang, et al. “A Robust Sparse Representation Model for Hyperspectral Image Classification.” SENSORS, vol. 17, no. 9, MDPI AG, 2017, doi:10.3390/s17092087.
- APA
- Huang, S., Zhang, H., & Pizurica, A. (2017). A robust sparse representation model for hyperspectral image classification. SENSORS, 17(9). https://doi.org/10.3390/s17092087
- Chicago author-date
- Huang, Shaoguang, Hongyan Zhang, and Aleksandra Pizurica. 2017. “A Robust Sparse Representation Model for Hyperspectral Image Classification.” SENSORS 17 (9). https://doi.org/10.3390/s17092087.
- Chicago author-date (all authors)
- Huang, Shaoguang, Hongyan Zhang, and Aleksandra Pizurica. 2017. “A Robust Sparse Representation Model for Hyperspectral Image Classification.” SENSORS 17 (9). doi:10.3390/s17092087.
- Vancouver
- 1.Huang S, Zhang H, Pizurica A. A robust sparse representation model for hyperspectral image classification. SENSORS. 2017;17(9).
- IEEE
- [1]S. Huang, H. Zhang, and A. Pizurica, “A robust sparse representation model for hyperspectral image classification,” SENSORS, vol. 17, no. 9, 2017.
@article{8537836,
articleno = {{2087}},
author = {{Huang, Shaoguang and Zhang, Hongyan and Pizurica, Aleksandra}},
issn = {{1424-8220}},
journal = {{SENSORS}},
keywords = {{REMOTE-SENSING IMAGES,MORPHOLOGICAL PROFILES,VECTOR MACHINES,RECOVERY,PURSUIT,SUPPORT,FUSION}},
language = {{eng}},
number = {{9}},
publisher = {{MDPI AG}},
title = {{A robust sparse representation model for hyperspectral image classification}},
url = {{http://doi.org/10.3390/s17092087}},
volume = {{17}},
year = {{2017}},
}
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