Multi Label Image Classification On 2
평가 지표
F1 Score
mAP (micro)
평가 결과
이 벤치마크에서 각 모델의 성능 결과
모델 이름 | F1 Score | mAP (micro) | Paper Title | Repository |
|---|---|---|---|---|
| FG-MAE (ViT-S/16) | 80.8 | 89.3 | Feature Guided Masked Autoencoder for Self-supervised Learning in Remote Sensing | - |
| MoCov3 (ViT-S/16) | 80.5 | 89.3 | SSL4EO-S12: A Large-Scale Multi-Modal, Multi-Temporal Dataset for Self-Supervised Learning in Earth Observation | - |
| ResNet50 | 76.8 | - | Benchmarking and scaling of deep learning models for land cover image classification | - |
| MAE (ViT-S/16) | 79.9 | 88.6 | Feature Guided Masked Autoencoder for Self-supervised Learning in Remote Sensing | - |
| ViT-S/16 | 78.9 | 87.8 | Feature Guided Masked Autoencoder for Self-supervised Learning in Remote Sensing | - |
| MoCov2 (ResNet50) | 79.8 | 88.7 | SSL4EO-S12: A Large-Scale Multi-Modal, Multi-Temporal Dataset for Self-Supervised Learning in Earth Observation | - |
0 of 6 row(s) selected.