Affinity Matrix Learning Via Nonnegative Matrix Factorization for Hyperspectral Imagery Clustering-Reference-Cited by-同舟云学术

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Affinity Matrix Learning Via Nonnegative Matrix Factorization for Hyperspectral Imagery Clustering

Published:2021 Issue: Volume:14 Page:402-415
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Qin Yao^ORCID,Li Biao,Ni Weiping,Quan Sinong^ORCID,Wang Peizhong,Bian Hui

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atmospheric Science,Computers in Earth Sciences

Link

http://xplorestaging.ieee.org/ielx7/4609443/9314330/09268461.pdf?arnumber=9268461

Cited by 13 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. The rise of nonnegative matrix factorization: Algorithms and applications;Information Systems;2024-07

2. Graph-Constrained Residual Self-Expressive Subspace Clustering Network for Hyperspectral Images;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

3. Contrastive Multiview Subspace Clustering of Hyperspectral Images Based on Graph Convolutional Networks;IEEE Transactions on Geoscience and Remote Sensing;2024

4. From Model-Based Optimization Algorithms to Deep Learning Models for Clustering Hyperspectral Images;Remote Sensing;2023-05-29

5. Nearest Neighboring Self-Supervised Learning for Hyperspectral Image Classification;Remote Sensing;2023-03-22

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