KGTN-ens: Few-Shot Image Classification with Knowledge Graph Ensembles
KGTN-ens: Few-Shot Image Classification with Knowledge Graph Ensembles
Dominik Filipiak Anna Fensel Agata Filipowska

Abstract
We propose KGTN-ens, a framework extending the recent Knowledge Graph Transfer Network (KGTN) in order to incorporate multiple knowledge graph embeddings at a small cost. We evaluate it with different combinations of embeddings in a few-shot image classification task. We also construct a new knowledge source - Wikidata embeddings - and evaluate it with KGTN and KGTN-ens. Our approach outperforms KGTN in terms of the top-5 accuracy on the ImageNet-FS dataset for the majority of tested settings.
Code Repositories
Benchmarks
| Benchmark | Methodology | Metrics |
|---|---|---|
| few-shot-image-classification-on-imagenet-fs | KGTN-ens (ResNet-50, h+g, max) | Top-5 Accuracy (%): 62.73 |
| few-shot-image-classification-on-imagenet-fs-1 | KGTN-ens (ResNet-50, h+g, max) | Top-5 Accuracy (%): 71.48 |
| few-shot-image-classification-on-imagenet-fs-2 | KGTN-ens (ResNet-50, h+g, mean) | Top-5 Accuracy (%): 78.90 |
| few-shot-image-classification-on-imagenet-fs-3 | KGTN-ens (ResNet-50, h+g, max) | Top-5 Accuracy (%): 82.56 |
| few-shot-image-classification-on-imagenet-fs-4 | KGTN-ens (ResNet-50, h+g, max) | Top-5 Accuracy (%): 68.58 |
| few-shot-image-classification-on-imagenet-fs-5 | KGTN-ens (ResNet-50, h+g, max) | Top-5 Accuracy (%): 75.45 |
| few-shot-image-classification-on-imagenet-fs-6 | KGTN-ens (ResNet-50, h+g, max) | Top-5 Accuracy (%): 81.12 |
| few-shot-image-classification-on-imagenet-fs-7 | KGTN-ens (ResNet-50, h+g, max) | Top-5 Accuracy (%): 83.46 |
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