| Dataset Name | SOTA Method | Metric | Trend | ||
|---|---|---|---|---|---|
| Nanjing National (test) | Training Time (s)0.03 | 15 | 1mo ago | ||
| Changshu National (test) | Training Time (s)0.03 | 15 | 1mo ago | ||
| Changshu Mobile (test) | Training Time (s)0.03 | 15 | 1mo ago | ||
| Nanjing Mobile | Training Time (s)0.03 | 15 | 1mo ago | ||
| Remote Sensing Dataset (test) | ViT-ICKy | Pearson R0.68 | 9 | 1mo ago | |
| Ancona (3-Day split) | NeuroDDAF | MAE3.14 | 7 | 17d ago | |
| Ancona 2-Day | NeuroDDAF | MAE3.01 | 7 | 17d ago | |
| Ancona 1-Day | NeuroDDAF | MAE2.61 | 7 | 17d ago | |
| Tianjin (3-Day) | NeuroDDAF | MAE37.27 | 7 | 17d ago | |
| Tianjin (2-Day) | NeuroDDAF | MAE34.09 | 7 | 17d ago | |
| Tianjin 1-Day | NeuroDDAF | MAE28.29 | 7 | 17d ago | |
| Shenzhen 3-Day | NeuroDDAF | MAE12.69 | 7 | 17d ago | |
| Shenzhen (2-Day) | NeuroDDAF | MAE12.27 | 7 | 17d ago | |
| Shenzhen 1-Day | AirPhyNet | MAE10.55 | 7 | 17d ago | |
| DALTON | STE(Ours) | RMSE30.43 | 4 | 1mo ago | |
| Nanjing National | - | Training Time (s)- | 0 | 1mo ago | |
| Changshu National | - | Training Time (second)- | 0 | 1mo ago | |
| Changshu Mobile | - | Training Time (s)- | 0 | 1mo ago |
