cub-200-2011 is a state-of-the-art machine learning benchmark indexed on Codesota. This page tracks published model results, top scores per metric, and the SOTA timeline for cub-200-2011.
Top 1 Accuracy is the reported evaluation metric for cub-200-2011. Codesota tracks published model scores on this metric so readers can compare state-of-the-art results across sources and model families.
Higher is better
| Rank | Model | Trust | Score | Year | Links | Fix |
|---|---|---|---|---|---|---|
| 01 | Q-SENN | verified | 85.9 | 2023 | Paper ↗Code ↗ | Looks wrong? |
| 02 | SLDD-Model | verified | 85.7 | 2023 | Paper ↗Code ↗ | Looks wrong? |
Accuracy is the reported evaluation metric for cub-200-2011. Codesota tracks published model scores on this metric so readers can compare state-of-the-art results across sources and model families.
Higher is better
| Rank | Model | Trust | Score | Year | Links | Fix |
|---|---|---|---|---|---|---|
| 01 | Bert | verified | 65 | 2020 | Paper ↗Code ↗ | Looks wrong? |