Abstract: Graph Neural Networks (GNNs) are rapidly becoming essential tools in deep learning, but their effectiveness when applied to images is often limited by challenges in graph representation.
Abstract: Hyperspectral image classification demands models capable of efficiently capturing complex spectral–spatial relationships and long-range dependencies. Despite significant advances in CNNs ...