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ResearchFormerly WizWand

Image Classification on SVHN (Natural and PGD-50-10 Robustness)

95.09Accuracy (Natural)RS-FGSM
79.479683.532387.58591.6377Apr 11, 2024
Updated 8mo ago

Evaluation results

MethodLinks
RS-FGSMnoise magnitude=4/255, Backbone=PreActResNet-18, Threat model=L_inf, Number of random seeds=32024.0495.0971.28
RS-AAERnoise magnitude=4/255, Backbone=PreActResNet-18, Threat model=L_inf, Number of random seeds=32024.0494.9971.97
MultiGradnoise magnitude=8/255, Backbone=PreActResNet-18, Threat model=L_inf, Number of random seeds=32024.0494.8611.49
ZeroGradnoise magnitude=4/255, Backbone=PreActResNet-18, Threat model=L_inf, Number of random seeds=32024.0494.8171.59
MultiGradnoise magnitude=4/255, Backbone=PreActResNet-18, Threat model=L_inf, Number of random seeds=32024.0494.7171.98
PGD-2noise magnitude=4/255, Backbone=PreActResNet-18, Threat model=L_inf, Number of random seeds=32024.0494.6673.29
PGD-2noise magnitude=8/255, Backbone=PreActResNet-18, Threat model=L_inf, Number of random seeds=32024.0494.6320.68
Grad Alignnoise magnitude=4/255, Backbone=PreActResNet-18, Threat model=L_inf, Number of random seeds=32024.0494.5672.12
N-FGSMnoise magnitude=4/255, Backbone=PreActResNet-18, Threat model=L_inf, Number of random seeds=32024.0494.5472.53
MultiGradnoise magnitude=12/255, Backbone=PreActResNet-18, Threat model=L_inf, Number of random seeds=32024.0494.480
RS-FGSMnoise magnitude=8/255, Backbone=PreActResNet-18, Threat model=L_inf, Number of random seeds=32024.0494.460
PGD-10noise magnitude=4/255, Backbone=PreActResNet-18, Threat model=L_inf, Number of random seeds=32024.0494.3774.76
N-AAERnoise magnitude=4/255, Backbone=PreActResNet-18, Threat model=L_inf, Number of random seeds=32024.0494.3573.1
PGD-2noise magnitude=12/255, Backbone=PreActResNet-18, Threat model=L_inf, Number of random seeds=32024.0494.160.02
FreeATnoise magnitude=4/255, Backbone=PreActResNet-18, Threat model=L_inf, Number of random seeds=32024.0493.6671.61
RS-FGSMnoise magnitude=12/255, Backbone=PreActResNet-18, Threat model=L_inf, Number of random seeds=32024.0492.740
ZeroGradnoise magnitude=8/255, Backbone=PreActResNet-18, Threat model=L_inf, Number of random seeds=32024.0492.4235.93
FreeATnoise magnitude=12/255, Backbone=PreActResNet-18, Threat model=L_inf, Number of random seeds=32024.0492.360
FreeATnoise magnitude=8/255, Backbone=PreActResNet-18, Threat model=L_inf, Number of random seeds=32024.0491.290.01
RS-AAERnoise magnitude=8/255, Backbone=PreActResNet-18, Threat model=L_inf, Number of random seeds=32024.0490.1141.75
Grad Alignnoise magnitude=8/255, Backbone=PreActResNet-18, Threat model=L_inf, Number of random seeds=32024.0490.143.85
PGD-10noise magnitude=8/255, Backbone=PreActResNet-18, Threat model=L_inf, Number of random seeds=32024.0489.6753.95
N-FGSMnoise magnitude=8/255, Backbone=PreActResNet-18, Threat model=L_inf, Number of random seeds=32024.0489.5645.63
N-AAERnoise magnitude=8/255, Backbone=PreActResNet-18, Threat model=L_inf, Number of random seeds=32024.0489.2646.98
ZeroGradnoise magnitude=12/255, Backbone=PreActResNet-18, Threat model=L_inf, Number of random seeds=32024.0488.0914.14
Grad Alignnoise magnitude=12/255, Backbone=PreActResNet-18, Threat model=L_inf, Number of random seeds=32024.0484.0123.62
RS-AAERnoise magnitude=12/255, Backbone=PreActResNet-18, Threat model=L_inf, Number of random seeds=32024.0483.522.84
N-AAERnoise magnitude=12/255, Backbone=PreActResNet-18, Threat model=L_inf, Number of random seeds=32024.0482.7626.87
N-FGSMnoise magnitude=12/255, Backbone=PreActResNet-18, Threat model=L_inf, Number of random seeds=32024.0481.4826.13
PGD-10noise magnitude=12/255, Backbone=PreActResNet-18, Threat model=L_inf, Number of random seeds=32024.0480.0837.65