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ResearchFormerly WizWand

Image Classification on SVHN (Gauss, SUAP, GSUAP, VIP)

68.4GaussGSUAP
7.5623.35539.1554.945May 15, 2026
Updated 5mo ago

Evaluation results

MethodLinks
GSUAPModel=ResNet-50, Ratio (%)=202026.0568.425.310.896.6
GSUAPModel=ViT-Tiny, Ratio (%)=202026.0567.819.824.196.3
GSUAPModel=ResNet-50, Ratio (%)=402026.0565.821.49.596.6
GSUAPModel=ResNet-18, Ratio (%)=202026.0564.613.28.196.1
GSUAPModel=ResNet-18, Ratio (%)=402026.0560.311.17.496.1
GSUAPModel=ResNet-50, Ratio (%)=602026.0559.419.49.896.6
GSUAPModel=ResNet-50, Ratio (%)=802026.0552.719.29.596.6
GSUAPModel=ResNet-18, Ratio (%)=602026.0550.810.97.296.1
GSUAPModel=ResNet-50, Ratio (%)=1002026.0548.619.29.496.6
GSUAPModel=ResNet-18, Ratio (%)=802026.0546.510.86.696.1
GSUAPModel=ResNet-18, Ratio (%)=1002026.054410.86.696.1
GSUAPModel=ViT-Small, Ratio (%)=202026.0543.723.621.897.6
GSUAPModel=ViT-Tiny, Ratio (%)=402026.054318.418.196.3
GSUAPModel=ViT-Tiny, Ratio (%)=602026.0532.511.210.896.3
GSUAPModel=AlexNet, Ratio (%)=202026.052815.710.595.4
GSUAPModel=AlexNet, Ratio (%)=402026.0527.311.77.395.4
GSUAPModel=AlexNet, Ratio (%)=602026.0526.88695.4
GSUAPModel=ViT-Tiny, Ratio (%)=802026.052610.310.896.3
GSUAPModel=ViT-Small, Ratio (%)=402026.0525.9222197.6
GSUAPModel=ViT-Tiny, Ratio (%)=1002026.0522.210.210.896.3
GSUAPModel=AlexNet, Ratio (%)=802026.0520.77.1695.4
GSUAPModel=ViT-Small, Ratio (%)=602026.052018.218.997.6
GSUAPModel=ViT-Small, Ratio (%)=802026.052013.214.697.6
GSUAPModel=ViT-Small, Ratio (%)=1002026.052013.21197.6
GSUAPModel=AlexNet, Ratio (%)=1002026.0516.77.1695.4
GSUAPModel=DenseNet, Ratio (%)=202026.0515.815.69.996.1
GSUAPModel=DenseNet, Ratio (%)=402026.0515.414.6896.1
GSUAPModel=DenseNet, Ratio (%)=602026.0513.114.17.796.1
GSUAPModel=DenseNet, Ratio (%)=802026.0510.59.47.696.1
GSUAPModel=DenseNet, Ratio (%)=1002026.059.98.57.796.1