Medical Image Classification on AUITD
98.33AccuracyLoRKD
Evaluation Results
| Method | Links | |
|---|---|---|
| LoRKDPre-train=Radimagenet, Params(M)=1.25, Comp. Ratio=5.32%2024.04 | 98.33 | |
| LoRKDPre-train=MedMnist, Params(M)=1.25, Comp. Ratio=5.32%2024.04 | 98.33 | |
| LoRKDPre-train=Med-MT, Params(M)=1.25, Comp. Ratio=5.32%2024.04 | 98.33 | |
| MTL-KDPre-train=MedMnist, Params(M)=1.25, Comp. Ratio=5.32%2024.04 | 98.05 | |
| KFPre-train=Med-MT, Params(M)=1.60, Comp. Ratio=6.81%2024.04 | 98.05 | |
| BaselinePre-train=Radimagenet, Params(M)=1.25, Comp. Ratio=5.32%2024.04 | 97.77 | |
| STLPre-train=Radimagenet, Params(M)=1.25, Comp. Ratio=5.32%2024.04 | 97.77 | |
| MTLPre-train=Radimagenet, Params(M)=1.25, Comp. Ratio=5.32%2024.04 | 97.77 | |
| BaselinePre-train=MedMnist, Params(M)=1.25, Comp. Ratio=5.32%2024.04 | 97.77 | |
| STLPre-train=MedMnist, Params(M)=1.25, Comp. Ratio=5.32%2024.04 | 97.77 | |
| MTLPre-train=MedMnist, Params(M)=1.25, Comp. Ratio=5.32%2024.04 | 97.77 | |
| MoCo-MTLPre-train=MedMnist, Params(M)=1.25, Comp. Ratio=5.32%2024.04 | 97.77 | |
| BaselinePre-train=Med-MT, Params(M)=1.25, Comp. Ratio=5.32%2024.04 | 97.77 | |
| MTL-KDPre-train=Med-MT, Params(M)=1.25, Comp. Ratio=5.32%2024.04 | 97.77 | |
| Aligned-MTLPre-train=Med-MT, Params(M)=1.25, Comp. Ratio=5.32%2024.04 | 97.77 | |
| STL-KDPre-train=MedMnist, Params(M)=1.25, Comp. Ratio=5.32%2024.04 | 97.49 | |
| MTLPre-train=Med-MT, Params(M)=1.25, Comp. Ratio=5.32%2024.04 | 97.49 | |
| MoCo-MTLPre-train=Med-MT, Params(M)=1.25, Comp. Ratio=5.32%2024.04 | 97.49 | |
| FoundationPre-train=Radimagenet, Params(M)=23.51, Comp. Ratio=/2024.04 | 96.66 | |
| STL-KDPre-train=Radimagenet, Params(M)=1.25, Comp. Ratio=5.32%2024.04 | 96.66 | |
| MTL-KDPre-train=Radimagenet, Params(M)=1.25, Comp. Ratio=5.32%2024.04 | 96.66 | |
| KFPre-train=Radimagenet, Params(M)=1.60, Comp. Ratio=6.81%2024.04 | 96.66 | |
| Aligned-MTLPre-train=MedMnist, Params(M)=1.25, Comp. Ratio=5.32%2024.04 | 96.37 | |
| KFPre-train=MedMnist, Params(M)=1.60, Comp. Ratio=6.81%2024.04 | 96.1 | |
| MoCo-MTLPre-train=Radimagenet, Params(M)=1.25, Comp. Ratio=5.32%2024.04 | 91.64 | |
| FoundationPre-train=Med-MT, Params(M)=23.51, Comp. Ratio=/2024.04 | 89.69 | |
| FoundationPre-train=MedMnist, Params(M)=23.51, Comp. Ratio=/2024.04 | 88.86 | |
| Aligned-MTLPre-train=Radimagenet, Params(M)=1.25, Comp. Ratio=5.32%2024.04 | 88.58 |