Combining diverse feature and graph representations from multiple extractors with GNNs and rank aggregation improves semi-supervised image classification accuracy.
Neighbor embedding projection and graph convolutional networks for image classification
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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation
Combining diverse feature and graph representations from multiple extractors with GNNs and rank aggregation improves semi-supervised image classification accuracy.