3D convolution attention-based multi-scale fusion network for hyperspectral image classification

Deep learning (DL) has significantly advanced pattern recognition and hyperspectral image (HSI) classification owing to its strong capability for hierarchical feature representation. However, existing DL-based HSI classification methods are often limited by scarce labeled samples, high parameter complexity, and the difficulty of learning discriminative features from high-dimensional spectral-spatial data. To address these challenges, this paper proposes a 3D convolution attention-based multi-sca