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Abstract: Graph Neural Networks (GNNs) have gained popularity as an efficient choice for learning on graph-structured data. However, most methods are node or graph-centered, often overlooking valuable ...
Abstract: Superpixel-based graph methods are efficient for hyperspectral image (HSI) classification, yet they often rely on static graph topologies fixed during preprocessing. These predetermined ...
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