Hyperspectral image (HSI) classification requires jointly capturing subtle spectral differences and complex spatial structures. Recent studies have introduced frequency-domain modeling to complement spatial–spectral representation learning. However, existing frequency-based methods still face some limitations. First, m...
Jin-Liang An, Deng-Ru Han, Long-Long Dai et al.· IEEE Transactions on Geoscie...· 0 citations
Recently, state space models (SSMs), particularly the Mamba architecture, have emerged as a powerful paradigm for hyperspectral image (HSI) classification due to their linear complexity and ability to capture long-range dependencies. However, existing Mamba-based approaches mainly rely on predefined geometric scanning...
Jinliang An, Long-Long Dai, Deng-Ru Han et al.· IEEE Transactions on Geoscie...· 0 citations
Object detection in optical remote sensing imagery is severely affected by adverse weather conditions, such as fog and haze, which degrade image quality and obscure structural details. Although recent Transformer-based detectors have achieved promising performance, they suffer from quadratic computational complexity fo...
Xiaopeng Yang, Qiang Zhang, Zheng Liang et al.· IEEE Signal Processing Lette...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
