Approximate sparse spectral clustering based on local information maintenance for hyperspectral image classification-Reference-Cited by-同舟云学术

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

Published:2018-08-17 Issue:8 Volume:13 Page:e0202161
ISSN:1932-6203
Container-title:PLOS ONE
language:en
Short-container-title:PLoS ONE

Author:

Yan Qing^ORCID,Ding Yun,Zhang Jing-Jing,Xun Li-Na,Zheng Chun-Hou

Funder

National Natural Science Foundation of China

AnHui University Youth Skeleton Teacher Project

China Postdoctoral Science Foundation

Anhui University Doctoral Scientific Research Start-up Funding

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

Reference29 articles.

1. Hyperspectral image super-resolution via non-negative structured sparse representation;W Dong;IEEE Transactions on Image Processing,2016

2. Gray wolf optimizer for hyperspectral band selection;SA Medjahed;Applied Soft Computing,2016

3. Clustering of Hyperspectral Images Based on Multiobjective Particle Swarm Optimization;A Paoli;IEEE Transactions on Geoscience & Remote Sensing,2009

4. A Comparison Study Between Two Hyperspectral Clustering Methods: KFCM and PSO-FCM;AA Naeini,2013

5. Na S, Xumin L, Yong G, editors. Research on k-means clustering algorithm: An improved k-means clustering algorithm. Intelligent Information Technology and Security Informatics (IITSI), 2010 Third International Symposium on; 2010: IEEE.

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An efficient feature fusion in HSI image classification;Multidimensional Systems and Signal Processing;2019-05-30

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