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A robust sparse representation model for hyperspectral image classification

(2017) SENSORS. 17(9).
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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:

MLA
Huang, Shaoguang, Hongyan Zhang, and Aleksandra Pizurica. “A Robust Sparse Representation Model for Hyperspectral Image Classification.” SENSORS 17.9 (2017): n. pag. Print.
APA
Huang, Shaoguang, Zhang, H., & Pizurica, A. (2017). A robust sparse representation model for hyperspectral image classification. SENSORS, 17(9).
Chicago author-date
Huang, Shaoguang, Hongyan Zhang, and Aleksandra Pizurica. 2017. “A Robust Sparse Representation Model for Hyperspectral Image Classification.” Sensors 17 (9).
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).
Vancouver
1.
Huang S, Zhang H, Pizurica A. A robust sparse representation model for hyperspectral image classification. SENSORS. MDPI AG; 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://dx.doi.org/10.3390/s17092087}},
  volume       = {{17}},
  year         = {{2017}},
}

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