Image Classification on ImageNet (50:950 split)
0.6536AccuracyMQ-Net
Evaluation Results
| Method | Links | |
|---|---|---|
| MQ-NetNoise Ratio=10%2022.10 | 0.6536 | |
| BADGENoise Ratio=10%2022.10 | 0.6484 | |
| SIMILARNoise Ratio=10%2022.10 | 0.6392 | |
| CORESETNoise Ratio=10%2022.10 | 0.6364 | |
| CONFNoise Ratio=10%2022.10 | 0.6356 | |
| LLNoise Ratio=10%2022.10 | 0.6328 | |
| MQ-NetNoise Ratio=20%2022.10 | 0.6308 | |
| RANDOMNoise Ratio=10%2022.10 | 0.6272 | |
| CONFNoise Ratio=20%2022.10 | 0.6256 | |
| CORESETNoise Ratio=20%2022.10 | 0.6224 | |
| CCALNoise Ratio=10%2022.10 | 0.6168 | |
| LLNoise Ratio=20%2022.10 | 0.6156 | |
| BADGENoise Ratio=20%2022.10 | 0.6148 | |
| SIMILARNoise Ratio=20%2022.10 | 0.614 | |
| CCALNoise Ratio=20%2022.10 | 0.607 | |
| RANDOMNoise Ratio=20%2022.10 | 0.6012 | |
| MQ-NetNoise Ratio=40%2022.10 | 0.5695 | |
| CCALNoise Ratio=40%2022.10 | 0.566 | |
| SIMILARNoise Ratio=40%2022.10 | 0.5648 | |
| LLNoise Ratio=40%2022.10 | 0.5568 | |
| CORESETNoise Ratio=40%2022.10 | 0.5532 | |
| MQ-NetNoise Ratio=60%2022.10 | 0.5411 | |
| RANDOMNoise Ratio=40%2022.10 | 0.5404 | |
| BADGENoise Ratio=40%2022.10 | 0.5404 | |
| SIMILARNoise Ratio=60%2022.10 | 0.5284 | |
| CCALNoise Ratio=60%2022.10 | 0.5116 | |
| CONFNoise Ratio=40%2022.10 | 0.5108 | |
| CORESETNoise Ratio=60%2022.10 | 0.4904 | |
| RANDOMNoise Ratio=60%2022.10 | 0.4824 | |
| BADGENoise Ratio=60%2022.10 | 0.478 | |
| LLNoise Ratio=60%2022.10 | 0.473 | |
| CONFNoise Ratio=60%2022.10 | 0.4504 |