Image Classification on CIFAR-10 uniform label noise, η=0.5 (test)
47.17AccuracyrSDNet
Evaluation results
| Method | Links | |
|---|---|---|
| rSDNetβ=0.05, λ=-12026.03 | 47.17 | |
| rSDNetβ=0, λ=-0.72026.03 | 46.31 | |
| rSDNetβ=0.05, λ=-0.82026.03 | 44.76 | |
| rSDNetβ=0.05, λ=-0.72026.03 | 42.01 | |
| rSDNetβ=0.1, λ=-12026.03 | 41.97 | |
| GCEq=0.72026.03 | 40.7 | |
| FCLµ=0.752026.03 | 40.54 | |
| rSDNetβ=0.1, λ=-0.82026.03 | 39.47 | |
| TCCEparameter=0.32026.03 | 39.38 | |
| TCCEparameter=0.22026.03 | 38.22 | |
| rSDNetβ=0.1, λ=-0.72026.03 | 38.04 | |
| GCEq=0.52026.03 | 36.76 | |
| rSDNetβ=0, λ=-0.52026.03 | 36.24 | |
| rSDNetβ=0, λ=-0.82026.03 | 35.78 | |
| FCLµ=0.52026.03 | 35.61 | |
| rSDNetβ=0.05, λ=-0.52026.03 | 35.44 | |
| TCCEparameter=0.12026.03 | 34.25 | |
| rSDNetβ=0.1, λ=-0.52026.03 | 33.72 | |
| rSDNetβ=0.3, λ=-12026.03 | 32.89 | |
| rSDNetβ=0.3, λ=-0.82026.03 | 32.59 | |
| rSDNetβ=0.3, λ=-0.72026.03 | 31.68 | |
| rSDNetβ=0.7, λ=-0.52026.03 | 31.64 | |
| rSDNetβ=0.7, λ=-12026.03 | 31.42 | |
| SCEα=0.5, β=12026.03 | 31.41 | |
| rSDNetβ=0.7, λ=-0.72026.03 | 31.38 | |
| rSDNetβ=0.5, λ=-12026.03 | 31.28 | |
| rSDNetβ=0.3, λ=-0.52026.03 | 31.27 | |
| rSDNetβ=1, λ=02026.03 | 31.24 | |
| rSDNetβ=0.5, λ=-0.82026.03 | 31.17 | |
| rSDNetβ=0.7, λ=02026.03 | 30.93 | |
| rSDNetβ=0.5, λ=-0.52026.03 | 30.92 | |
| FCLµ=0.252026.03 | 30.75 | |
| rSDNetβ=0.7, λ=-0.82026.03 | 30.74 | |
| rSDNetβ=0.5, λ=-0.72026.03 | 30.66 | |
| rSDNetβ=0.5, λ=02026.03 | 30.47 | |
| rSDNetβ=0.7, λ=0.52026.03 | 30.42 | |
| CCE2026.03 | 30.04 | |
| rSDNetβ=0.1, λ=02026.03 | 29.74 | |
| rSDNetβ=0.3, λ=02026.03 | 29.52 | |
| rSDNetβ=0.5, λ=0.52026.03 | 29.49 | |
| rKLD2026.03 | 26.95 | |
| FCLµ=02026.03 | 10 | |
| MAE2026.03 | 9.96 |