Image Classification on CIFAR-10 (4:6 split)
0.931AccuracyMQ-Net
Evaluation Results
| Method | Links | |
|---|---|---|
| MQ-NetNoise Ratio=10%2022.10 | 0.931 | |
| CONFNoise Ratio=10%2022.10 | 0.9283 | |
| BADGENoise Ratio=10%2022.10 | 0.928 | |
| MQ-NetNoise Ratio=20%2022.10 | 0.921 | |
| LLNoise Ratio=10%2022.10 | 0.9209 | |
| CORESETNoise Ratio=10%2022.10 | 0.9176 | |
| BADGENoise Ratio=20%2022.10 | 0.9173 | |
| CONFNoise Ratio=20%2022.10 | 0.9172 | |
| MQ-NetNoise Ratio=40%2022.10 | 0.9148 | |
| LLNoise Ratio=20%2022.10 | 0.9121 | |
| CORESETNoise Ratio=20%2022.10 | 0.9106 | |
| CCALNoise Ratio=10%2022.10 | 0.9055 | |
| CCALNoise Ratio=20%2022.10 | 0.8999 | |
| SIMILARNoise Ratio=10%2022.10 | 0.8992 | |
| RANDOMNoise Ratio=10%2022.10 | 0.8983 | |
| MQ-NetNoise Ratio=60%2022.10 | 0.8951 | |
| LLNoise Ratio=40%2022.10 | 0.8941 | |
| BADGENoise Ratio=40%2022.10 | 0.8927 | |
| SIMILARNoise Ratio=20%2022.10 | 0.8919 | |
| CORESETNoise Ratio=40%2022.10 | 0.8912 | |
| RANDOMNoise Ratio=20%2022.10 | 0.8906 | |
| CCALNoise Ratio=40%2022.10 | 0.8887 | |
| CONFNoise Ratio=40%2022.10 | 0.8869 | |
| SIMILARNoise Ratio=40%2022.10 | 0.8853 | |
| RANDOMNoise Ratio=40%2022.10 | 0.8773 | |
| CCALNoise Ratio=60%2022.10 | 0.8749 | |
| SIMILARNoise Ratio=60%2022.10 | 0.8738 | |
| LLNoise Ratio=60%2022.10 | 0.8695 | |
| BADGENoise Ratio=60%2022.10 | 0.8683 | |
| CORESETNoise Ratio=60%2022.10 | 0.865 | |
| RANDOMNoise Ratio=60%2022.10 | 0.8564 | |
| CONFNoise Ratio=60%2022.10 | 0.8543 |