2 citations · 4 across the 4 of their papers we have counts for
4 papers
When Genes Speak: A Semantic-Guided Framework for Spatially Resolved Transcriptomics Data Clustering
Jiangkai Long, Yanran Zhu, Chang Tang +3
Spatial transcriptomics enables gene expression profiling with spatial context, offering unprecedented insights into the tissue microenvironment. However, most computational models…
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…
Pixel-Superpixel Contrastive Learning and Pseudo-Label Correction for Hyperspectral Image Clustering
Renxiang Guan, Zihao Li, Xianju Li +1
Hyperspectral image (HSI) clustering is gaining considerable attention owing to recent methods that overcome the inefficiency and misleading results from the absence of supervised…
Contrastive Multi-view Subspace Clustering of Hyperspectral Images based on Graph Convolutional Networks
Renxiang Guan, Zihao Li, Xianju Li +2
High-dimensional and complex spectral structures make the clustering of hyperspectral images (HSI) a challenging task. Subspace clustering is an effective approach for addressing t…