SAR Ship Classification on FuSARShip 4-class (test)
69.54F1 ScoreM2mu
Evaluation Results
| Method | Links | |
|---|---|---|
| M2muBackbone=VGG16, Input Resolution=64x64, Pre-training=True2025.08 | 69.54 | |
| M2mfBackbone=ViT-16 base224, Input Resolution=224x224, Pre-training=True2025.08 | 67.88 | |
| M2mfBackbone=VGG16, Input Resolution=64x64, Pre-training=True2025.08 | 63.3 | |
| M2morigBackbone=VGG16, Input Resolution=64x64, Pre-training=True2025.08 | 62.72 | |
| M2muBackbone=ViT-16 base224, Input Resolution=224x224, Pre-training=True2025.08 | 61.79 | |
| BaselineBackbone=VGG16, Input Resolution=64x64, Pre-training=True2025.08 | 60.91 | |
| M2morigBackbone=ViT-16 base224, Input Resolution=224x224, Pre-training=True2025.08 | 53.23 | |
| BaselineBackbone=ResNet50, Input Resolution=64x64, Pre-training=True2025.08 | 48.39 | |
| BaselineBackbone=ViT-16 base224, Input Resolution=224x224, Pre-training=True2025.08 | 42.61 | |
| M2mfBackbone=ResNet50, Input Resolution=64x64, Pre-training=True2025.08 | 42.61 | |
| M2muBackbone=ResNet50, Input Resolution=64x64, Pre-training=True2025.08 | 42.61 | |
| M2morigBackbone=ResNet50, Input Resolution=64x64, Pre-training=True2025.08 | 12.3 |