Spatial-Spectral Clustering With Anchor Graph for Hyperspectral Image-Reference-Cited by-同舟云学术

Spatial-Spectral Clustering With Anchor Graph for Hyperspectral Image

Published:2022 Issue: Volume:60 Page:1-13
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Wang Qi¹^ORCID,Miao Yanling²^ORCID,Chen Mulin¹^ORCID,Yuan Yuan¹

Affiliation:

1. School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi’an, China

2. School of Computer Science and the School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi’an, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/9633014/09931151.pdf?arnumber=9931151

Reference53 articles.

1. Mineral Mapping with Hyperspectral Image Based on an Improved K-Means Clustering Algorithm

2. Sparsity-Based Clustering for Large Hyperspectral Remote Sensing Images

3. Scalable Graph-Based Clustering With Nonnegative Relaxation for Large Hyperspectral Image

4. Fast semi-supervised learning with anchor graph for large hyperspectral images

5. Large graph construction for scalable semi-supervised learning;liu;Proc 27th Int Conf Mach Learn,2010

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