Deep Spatial-Spectral Subspace Clustering for Hyperspectral Images Based on Contrastive Learning

Hyperspectral image (HSI) clustering is a major challenge due to the redundant spectral information in HSIs. In this paper, we propose a novel deep subspace clustering method that extracts spatial–spectral features via contrastive learning. First, we construct positive and negative sample pairs thro...

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Auteurs principaux: Xiang Hu, Teng Li, Tong Zhou, Yuanxi Peng
Format: article
Langue:EN
Publié: MDPI AG 2021
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Accès en ligne:https://doaj.org/article/c6301634536045f89cc5770378d53257
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