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Patch Classification on OpenSRH (test)

83.1Clean Accuracy[17]
43.309653.639863.9774.3002Mar 13, 2025

Evaluation results

MethodLinks
[17]Training=from Scratch, Model=ResNet-502025.0383.182.2910.259.8410.279.8511.1510.345.525.015.575.025.975.31
[17]Training=from ImageNet weights, Model=ResNet-502025.0380.0777.7823.6122.1123.3221.8421.7621.0313.0712.813.0612.7512.5312.71
[17]Training=from ImageNet weights, Model=WideResNet-502025.0379.2476.4632.2826.5332.2426.5128.9523.8620.8717.2120.917.2519.2415.97
HSATTraining=from ImageNet weights, Model=WideResNet-502025.0368.3567.7660.5159.2760.5459.3261.4460.1953.1351.2653.1251.2654.4452.73
HSATTraining=from ImageNet weights, Model=ResNet-502025.0366.4866.3364.0761.3664.1161.465.1162.456.975556.9855.0457.9256.06
HSATTraining=from Scratch, Model=ResNet-502025.0366.4365.6164.0761.3664.1161.465.1162.457.1853.4857.153.3858.5254.76
HSAT-PatchTraining=from ImageNet weights, Model=ResNet-502025.0350.844.3651.0844.9551.0644.9451.144.9650.2945.2250.2945.2250.4145.31
HSAT-PatchTraining=from Scratch, Model=ResNet-502025.0344.8439.6344.6739.6544.6739.6544.839.844.2339.7644.2239.7544.2639.88