Semi-supervised Image Classification on Flowers 10% (train)
98.18AccuracyGRaNDe
Evaluation Results
| Method | Links | |
|---|---|---|
| GRaNDeFeatures=ViT-B162026.05 | 98.18 | |
| DGCGFeatures=ViT-B162026.05 | 98.09 | |
| WSEFFeatures=ViT-B162026.05 | 97.82 | |
| MGCNFeatures=ViT-B162026.05 | 97.43 | |
| PL+ SGDFeatures=ViT-B162026.05 | 96.84 | |
| SVMFeatures=ViT-B162026.05 | 96.75 | |
| GNN-LDSFeatures=ViT-B162026.05 | 96.66 | |
| OPFFeatures=ViT-B162026.05 | 96.5 | |
| LS+ kNNFeatures=ViT-B162026.05 | 95.74 | |
| LS+ ML-Perc.Features=ViT-B162026.05 | 95.13 | |
| LS+ SVMFeatures=ViT-B162026.05 | 94.49 | |
| LS+ OPFFeatures=ViT-B162026.05 | 94.22 | |
| ML-Perc.Features=ViT-B162026.05 | 92.59 | |
| GRaNDeFeatures=ResNet2026.05 | 86.19 | |
| MGCNFeatures=ResNet2026.05 | 85.88 | |
| DGCGFeatures=ResNet2026.05 | 85.68 | |
| WSEFFeatures=ResNet2026.05 | 85.12 | |
| PL+ SGDFeatures=ResNet2026.05 | 82.69 | |
| CoMatch2026.05 | 82.55 | |
| SVMFeatures=ResNet2026.05 | 80.54 | |
| GRaNDeFeatures=SENet2026.05 | 80.1 | |
| GNN-LDSFeatures=ResNet2026.05 | 79.32 | |
| ML-Perc.Features=ResNet2026.05 | 78.88 | |
| MGCNFeatures=SENet2026.05 | 78.82 | |
| DGCGFeatures=SENet2026.05 | 78.42 | |
| PL+ SGDFeatures=SENet2026.05 | 76.87 | |
| WSEFFeatures=SENet2026.05 | 76.16 | |
| GNN-LDSFeatures=SENet2026.05 | 73.69 | |
| LS+ SVMFeatures=ResNet2026.05 | 73.53 | |
| LS+ kNNFeatures=ResNet2026.05 | 73.49 | |
| SVMFeatures=SENet2026.05 | 73.3 | |
| LS+ ML-Perc.Features=ResNet2026.05 | 73.03 | |
| LS+ OPFFeatures=ResNet2026.05 | 72.66 | |
| ML-Perc.Features=SENet2026.05 | 72.62 | |
| OPFFeatures=ResNet2026.05 | 71.77 | |
| OPFFeatures=SENet2026.05 | 64 | |
| LS+ SVMFeatures=SENet2026.05 | 59.84 | |
| LS+ ML-Perc.Features=SENet2026.05 | 59.39 | |
| LS+ OPFFeatures=SENet2026.05 | 59.25 | |
| LS+ kNNFeatures=SENet2026.05 | 58.05 |