Approximate sparse spectral clustering based on local information maintenance for hyperspectral image classification

Sparse spectral clustering (SSC) has become one of the most popular clustering approaches in recent years. However, its high computational complexity prevents its application to large-scale datasets such as hyperspectral images (HSIs). In this paper, we propose two efficient approximate sparse spect...

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Detalles Bibliográficos
Autores principales: Yan, Qing, Ding, Yun, Zhang, Jing-Jing, Xun, Li-Na, Zheng, Chun-Hou
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6097666/
https://www.ncbi.nlm.nih.gov/pubmed/30118492
http://dx.doi.org/10.1371/journal.pone.0202161

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6097666/
https://www.ncbi.nlm.nih.gov/pubmed/30118492
http://dx.doi.org/10.1371/journal.pone.0202161

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