2 citations · 7 across the 7 of their papers we have counts for
7 papers
FreCT: Frequency-augmented Convolutional Transformer for Robust Time Series Anomaly Detection
Wenxin Zhang, Ding Xu, Guangzhen Yao +6
Time series anomaly detection is critical for system monitoring and risk identification, across various domains, such as finance and healthcare. However, for most reconstruction-ba…
A Novel Scene Coupling Semantic Mask Network for Remote Sensing Image Segmentation
Xiaowen Ma, Rongrong Lian, Zhenkai Wu +8
As a common method in the field of computer vision, spatial attention mechanism has been widely used in semantic segmentation of remote sensing images due to its outstanding long-r…
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…
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…
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…
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…