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ResearchFormerly WizWand

Medical Image Classification on AUITD

98.33AccuracyLoRKD
88.1990.822593.45596.0875Apr 26, 2024
Updated 8mo ago

Evaluation results

MethodLinks
LoRKDPre-train=Radimagenet, Params(M)=1.25, Comp. Ratio=5.32%2024.0498.33
LoRKDPre-train=MedMnist, Params(M)=1.25, Comp. Ratio=5.32%2024.0498.33
LoRKDPre-train=Med-MT, Params(M)=1.25, Comp. Ratio=5.32%2024.0498.33
MTL-KDPre-train=MedMnist, Params(M)=1.25, Comp. Ratio=5.32%2024.0498.05
KFPre-train=Med-MT, Params(M)=1.60, Comp. Ratio=6.81%2024.0498.05
BaselinePre-train=Radimagenet, Params(M)=1.25, Comp. Ratio=5.32%2024.0497.77
STLPre-train=Radimagenet, Params(M)=1.25, Comp. Ratio=5.32%2024.0497.77
MTLPre-train=Radimagenet, Params(M)=1.25, Comp. Ratio=5.32%2024.0497.77
BaselinePre-train=MedMnist, Params(M)=1.25, Comp. Ratio=5.32%2024.0497.77
STLPre-train=MedMnist, Params(M)=1.25, Comp. Ratio=5.32%2024.0497.77
MTLPre-train=MedMnist, Params(M)=1.25, Comp. Ratio=5.32%2024.0497.77
MoCo-MTLPre-train=MedMnist, Params(M)=1.25, Comp. Ratio=5.32%2024.0497.77
BaselinePre-train=Med-MT, Params(M)=1.25, Comp. Ratio=5.32%2024.0497.77
MTL-KDPre-train=Med-MT, Params(M)=1.25, Comp. Ratio=5.32%2024.0497.77
Aligned-MTLPre-train=Med-MT, Params(M)=1.25, Comp. Ratio=5.32%2024.0497.77
STL-KDPre-train=MedMnist, Params(M)=1.25, Comp. Ratio=5.32%2024.0497.49
MTLPre-train=Med-MT, Params(M)=1.25, Comp. Ratio=5.32%2024.0497.49
MoCo-MTLPre-train=Med-MT, Params(M)=1.25, Comp. Ratio=5.32%2024.0497.49
FoundationPre-train=Radimagenet, Params(M)=23.51, Comp. Ratio=/2024.0496.66
STL-KDPre-train=Radimagenet, Params(M)=1.25, Comp. Ratio=5.32%2024.0496.66
MTL-KDPre-train=Radimagenet, Params(M)=1.25, Comp. Ratio=5.32%2024.0496.66
KFPre-train=Radimagenet, Params(M)=1.60, Comp. Ratio=6.81%2024.0496.66
Aligned-MTLPre-train=MedMnist, Params(M)=1.25, Comp. Ratio=5.32%2024.0496.37
KFPre-train=MedMnist, Params(M)=1.60, Comp. Ratio=6.81%2024.0496.1
MoCo-MTLPre-train=Radimagenet, Params(M)=1.25, Comp. Ratio=5.32%2024.0491.64
FoundationPre-train=Med-MT, Params(M)=23.51, Comp. Ratio=/2024.0489.69
FoundationPre-train=MedMnist, Params(M)=23.51, Comp. Ratio=/2024.0488.86
Aligned-MTLPre-train=Radimagenet, Params(M)=1.25, Comp. Ratio=5.32%2024.0488.58