2 citations · 7 across the 7 of their papers we have counts for
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cs.CV2024★ 1 cited
Multi-level Graph Subspace Contrastive Learning for Hyperspectral Image Clustering
Jingxin Wang, Renxiang Guan, Kainan Gao +4
Hyperspectral image (HSI) clustering is a challenging task due to its high complexity. Despite subspace clustering shows impressive performance for HSI, traditional methods tend to…
cs.CV2024★ 1 cited
S2RC-GCN: A Spatial-Spectral Reliable Contrastive Graph Convolutional Network for Complex Land Cover Classification Using Hyperspectral Images
Renxiang Guan, Zihao Li, Chujia Song +3
Spatial correlations between different ground objects are an important feature of mining land cover research. Graph Convolutional Networks (GCNs) can effectively capture such spati…
cs.CV2024
Multiview Subspace Clustering of Hyperspectral Images based on Graph Convolutional Networks
Xianju Li, Renxiang Guan, Zihao Li +2
High-dimensional and complex spectral structures make clustering of hy-perspectral images (HSI) a challenging task. Subspace clustering has been shown to be an effective approach f…