Row, column, and Cartesian product graphs built from lagged pixel correlations improve GNN image classification accuracy over grid and superpixel graphs on MNIST and Fashion-MNIST, with one exception.
We achieve this by inferring the underlying graph for im- ages using the correlation method in [5, 6]
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Inferring the Graph Structure of Images for Graph Neural Networks
Row, column, and Cartesian product graphs built from lagged pixel correlations improve GNN image classification accuracy over grid and superpixel graphs on MNIST and Fashion-MNIST, with one exception.