Self-Supervised Deep Subspace Clustering for Hyperspectral Images With Adaptive Self-Expressive Coefficient Matrix Initialization

Self-Supervised Deep Subspace Clustering for Hyperspectral Images With Adaptive Self-Expressive Coefficient Matrix Initialization

Deep subspace clustering network has shown its effectiveness in hyperspectral image (HSI) clustering. However, there are two major challenges that need to be addressed: 1) lack of effective supervision for feature learning; and 2) negative effect caused by the high redundancy of the global dictionar...

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Bibliographic Details
Main Authors: Kun Li, Yao Qin, Qiang Ling, Yingqian Wang, Zaiping Lin, Wei An
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Deep subspace clustering (DSC)
hyperspectral image (HSI)
self-expressive
self-supervised
subspace clustering (SC)
Online Access:https://ieeexplore.ieee.org/document/9371374/

Internet

https://ieeexplore.ieee.org/document/9371374/

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