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Fine Grained Image Classification On Foodx
Metrics
Accuracy (%)
Results
Performance results of various models on this benchmark
| Paper Title | Repository | ||
|---|---|---|---|
| CSWin-L | 79.90 | Learning Multi-Subset of Classes for Fine-Grained Food Recognition | - |
| VOLO-D5 | 79.15 | Learning Multi-Subset of Classes for Fine-Grained Food Recognition | - |
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