A5102674779- Remote-Sensing Image Classification
- Remote Sensing and Land Use
- Advanced Image Fusion Techniques
- Advanced Computational Techniques and Applications
- Autonomous Vehicle Technology and Safety
- Currency Recognition and Detection
- Environmental and Agricultural Sciences
- Building Energy and Comfort Optimization
- Environmental Changes in China
Nanjing University of Information Science and Technology
2024-2025
Institute of Optics and Electronics, Chinese Academy of Sciences
2024-2025
Heilongjiang Bayi Agricultural University
2024
Hyperspectral image (HSI) classification constitutes the fundamental research in remote sensing fields. Convolutional Neural Networks (CNNs) and Transformers have demonstrated impressive capability capturing spectral-spatial contextual dependencies. However, these architectures suffer from limited receptive fields quadratic computational complexity, respectively. Fortunately, recent Mamba built upon State Space Model integrate advantages of long-range sequence modeling linear efficiency,...
Hyperspectral image (HSI) classification has garnered substantial attention in remote sensing fields. Recent Mamba architectures built upon the Selective State Space Models (S6) have demonstrated enormous potential long-range sequence modeling. However, high dimensionality of hyperspectral data and information redundancy pose challenges to application HSI classification, suffering from suboptimal performance computational efficiency. In light this, this paper investigates a lightweight...