The collaborative classification of hyperspectral images (HSI) with a complementary modality such as light detection and ranging (LiDAR) or synthetic aperture radar (SAR), which is known as multi-source remote sensing image classification (MRSIC), can combine rich spectral information with structural cues and is helpfu...
Yan Mo, Zi-Yang Liu, Yu-Hao Liu et al.· Remote Sensing· 0 citations
Hyperspectral image (HSI) classification requires effective spectral–spatial representation learning under limited labeled samples and constrained computational resources. Existing Mamba-based methods generally preserve explicit sequence structures through dense or fixed tokens, but this may retain substantial spectral...
Chun-Chao Li, Lu-Lu Shi, Zhuo-Jun Xie et al.· IEEE Journal of Selected Top...· 0 citations
Hyperspectral anomaly detection (HAD) technique, which aims to identify abnormal targets that are different from the surrounding background in both spectral and spatial aspects, plays an important role in diverse remote sensing applications. Recently, a series of deep learning-based methods on the principle of backgrou...
Pu-Hong Duan, Zhi-Xiang Huang, Xu-Dong Kang et al.· IEEE Transactions on Pattern...· 0 citations
A systematic survey and diagnostic evaluation of MLLMs for RSISU and demonstrates the strong transferability of general-purpose CV-MLLMs and shows that current RS-MLLMs do not consistently outperform them across diverse RSISU tasks.
