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cs.CV2026
Hyperspectral Anomaly Detection via Group Sparse Low-Rank Tensor Factorization With Automatic Anomaly Grouping
Quan Yu, Yu-Hong Dai, Xiongjun Zhang
Low-rank tensor modeling has become an effective tool for hyperspectral anomaly detection. However, existing methods still suffer from high computational cost and limited flexibili…
cs.CV2025
Spectral-Spatial Extraction through Layered Tensor Decomposition for Hyperspectral Anomaly Detection
Quan Yu, Yu-Hong Dai, Minru Bai
Low rank tensor representation (LRTR) methods are very useful for hyperspectral anomaly detection (HAD). To overcome the limitations that they often overlook spectral anomaly and r…