l7170 Goto Github PK
Name: Li Lu
Type: User
Company: BeiJing Information Science & Technology University
Location: Beijing,China
Blog: [email protected]
Name: Li Lu
Type: User
Company: BeiJing Information Science & Technology University
Location: Beijing,China
Blog: [email protected]
A Cross Swin Transformer Based Siamese U-Shape Network for Change Detection in Remote Sensing Images
Low-Rank and Sparse Decomposition with Mixture-of-Gaussian for Hyperspectral Anomaly Detection
Multi-Scale Dense Graph Attention net- work (MSDesGAT) for hyperspectral classification
GPU Implementation of Large-Scale Abundance Estimation with Constraint Linear Spectral Mixture Model for Hyperspectral Unmixing
邻接操作算法库函数,大尺寸多维凸集连续优化算法
a prior-based tensor approximation (PTA) is proposed for hyperspectral anomaly detection, in which HSI is decomposed into a background tensor and an anomaly tensor. In the background tensor, a low-rank prior is incorporated into spectral dimension by truncated nuclear norm regularization, and a piecewise- smooth prior on spatial dimension can be embedded by a linear total variation-norm regularization. For anomaly tensor, it is unfolded along spectral dimension coupled with spatial group sparse prior that can be represented by l 2,1 -norm regularization.
Semi-Supervised Classfication for Hyperspectral image based on Segment-tree and SELF.
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