SAR Ship Classification on FuSARShip (2-class, test)
70.81F1-scoreM2mu
Evaluation Results
| Method | Links | |
|---|---|---|
| M2muBackbone=VGG16, Input Resolution=64x64, Pre-training=True2025.08 | 70.81 | |
| M2muBackbone=ViT-16 base224, Input Resolution=224x224, Pre-training=True2025.08 | 69.95 | |
| M2mfBackbone=ViT-16 base224, Input Resolution=224x224, Pre-training=True2025.08 | 69.37 | |
| M2mfBackbone=VGG16, Input Resolution=64x64, Pre-training=True2025.08 | 69.37 | |
| M2morigBackbone=VGG16, Input Resolution=64x64, Pre-training=True2025.08 | 68.7 | |
| M2morigBackbone=ViT-16 base224, Input Resolution=224x224, Pre-training=True2025.08 | 68.08 | |
| M2morigBackbone=ResNet50, Input Resolution=64x64, Pre-training=True2025.08 | 60.23 | |
| BaselineBackbone=VGG16, Input Resolution=64x64, Pre-training=True2025.08 | 57.23 | |
| BaselineBackbone=ViT-16 base224, Input Resolution=224x224, Pre-training=True2025.08 | 55.92 | |
| BaselineBackbone=ResNet50, Input Resolution=64x64, Pre-training=True2025.08 | 55.4 | |
| M2mfBackbone=ResNet50, Input Resolution=64x64, Pre-training=True2025.08 | 55.4 | |
| M2muBackbone=ResNet50, Input Resolution=64x64, Pre-training=True2025.08 | 55.4 |