Abstract: Graph neural networks (GNNs) could directly deal with the data of graph structure. Current GNNs are confined to the spatial domain and learn real low-dimensional embeddings in graph ...

Abstract: Graph convolutional networks (GCNs) have emerged as a prominent research focus for hyperspectral image classification (HSIC). However, existing GCN-based HSIC methods still face the ...