Semi Supervised Image Classification On Mini
평가 지표
Accuracy
평가 결과
이 벤치마크에서 각 모델의 성능 결과
모델 이름 | Accuracy | Paper Title | Repository |
|---|---|---|---|
| SemCo (μ=3) | 53.99±0.93 | All Labels Are Not Created Equal: Enhancing Semi-supervision via Label Grouping and Co-training | - |
| FeatMatch | 60.95 | FeatMatch: Feature-Based Augmentation for Semi-Supervised Learning | - |
| SimPLE | 66.55 | SimPLE: Similar Pseudo Label Exploitation for Semi-Supervised Classification | - |
| SemCo (μ=7) | 50.54±2.20 | All Labels Are Not Created Equal: Enhancing Semi-supervision via Label Grouping and Co-training | - |
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