Landmark-based large-scale sparse subspace clustering method for hyperspectral images
- Author
- Shaoguang Huang (UGent) , Hongyan Zhang and Aleksandra Pizurica (UGent)
- Organization
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Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-8623398
- MLA
- Huang, Shaoguang, Hongyan Zhang, and Aleksandra Pizurica. “Landmark-based Large-scale Sparse Subspace Clustering Method for Hyperspectral Images.” 2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS). 2019. Print.
- APA
- Huang, Shaoguang, Zhang, H., & Pizurica, A. (2019). Landmark-based large-scale sparse subspace clustering method for hyperspectral images. 2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS). Presented at the 2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS).
- Chicago author-date
- Huang, Shaoguang, Hongyan Zhang, and Aleksandra Pizurica. 2019. “Landmark-based Large-scale Sparse Subspace Clustering Method for Hyperspectral Images.” In 2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS).
- Chicago author-date (all authors)
- Huang, Shaoguang, Hongyan Zhang, and Aleksandra Pizurica. 2019. “Landmark-based Large-scale Sparse Subspace Clustering Method for Hyperspectral Images.” In 2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS).
- Vancouver
- 1.Huang S, Zhang H, Pizurica A. Landmark-based large-scale sparse subspace clustering method for hyperspectral images. 2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS). 2019.
- IEEE
- [1]S. Huang, H. Zhang, and A. Pizurica, “Landmark-based large-scale sparse subspace clustering method for hyperspectral images,” in 2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), Yokohama, Japan, 2019.
@inproceedings{8623398,
author = {Huang, Shaoguang and Zhang, Hongyan and Pizurica, Aleksandra},
booktitle = {2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS)},
issn = {2153-6996},
language = {eng},
location = {Yokohama, Japan},
pages = {4},
title = {Landmark-based large-scale sparse subspace clustering method for hyperspectral images},
year = {2019},
}