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Image Classification on STL10 (test)

4.82Error Rate (%)FlatMatch
2.023220.901639.7858.6584Jul 30, 2018Jun 13, 2019Apr 27, 2020Mar 12, 2021Jan 25, 2022Dec 10, 2022Oct 25, 2023

Evaluation results

MethodLinks
FlatMatch# Label=10002023.104.82———
FlatMatch (Fix label)# Label=10002023.104.82———
FlatMatch-e# Label=10002023.105.03———
FreeMatch# Label=10002023.105.63———
SoftMatch# Label=10002023.105.73———
FlexMatch# Label=10002023.105.77———
UDA# Label=10002023.106.25———
FixMatch# Label=10002023.106.39———
Dash# Label=10002023.106.64———
MPL# Label=10002023.106.66———
ReMixMatch# Label=10002023.106.74———
SESN-B# Params=11.0 M, Projection type=maximum scalar projection2019.108.51———
Harm WRN# Params=11.0 M2019.109.55———
SESN-A# Params=11.0 M, Feature type=vector2019.1010.83———
DSS# Params=11.0 M2019.1011.28———
WRN# Params=11.0 M2019.1011.48———
SiCNN# Params=11.0 M2019.1011.62———
SI-ConvNet# Params=11.0 M2019.1012.48———
SESN-C# Params=11.0 M, Interaction=interscale interaction2019.1014.08———
FlatMatch (Fix label)# Label=402023.1014.96———
FreeMatch# Label=402023.1015.56———
HybridNetNb. labeled images=1000, Backbone=ResNet2018.0715.9———
FlatMatch# Label=402023.1016.2———
FlatMatch-e# Label=402023.1016.32———
Mean Teacher ResNetNb. labeled images=1000, Backbone=ResNet, reproduced_by_authors=true2018.0716.8———
ResNet baselineNb. labeled images=1000, Backbone=ResNet2018.0718———
PNGPredict from=reconstructions2021.0619.214.21—
BINCEPredict from=features2021.0619.20.12121.1—
JPEGPredict from=reconstructions2021.0619.94.63—
WebPPredict from=reconstructions2021.0620.31.1212.7—
SoftMatch# Label=402023.1021.42———
MixMatch# Label=10002023.1021.7———
SS-CNN# Params=10.8 M2019.1025.47———
SWWAENb. labeled images=10002018.0725.67———
FlexMatch# Label=402023.1029.15———
ReMixMatch# Label=402023.1032.12———
Pseudo Label# Label=10002023.1032.64———
Π-Model# Label=10002023.1032.78———
Mean Teacher# Label=10002023.1033.9———
FixMatch# Label=402023.1034.52———
VICPredict from=features2021.0635.30.08174.8—
MPL# Label=402023.1035.76———
UDA# Label=402023.1035.97———
Dash# Label=402023.1037.42———
VAT# Label=10002023.1037.95———
VCPredict from=reconstructions2021.0640.20.2362.8—
VICPredict from=reconstructions2021.0644.30.05268.6—
VCPredict from=features2021.0652.61.0813.2—
MixMatch# Label=402023.1054.93———
Mean Teacher# Label=402023.1071.72———
Π-Model# Label=402023.1074.31———
Pseudo Label# Label=402023.1074.68———
VAT# Label=402023.1074.74———
Fixed ETFNetwork=ResNet50, Epochs=502024.11———58.11
Fixed ETFNetwork=ResNet50, Epochs=2002024.11———64.33
Fixed ETFNetwork=VGG13, Epochs=502024.11———66.15
Fixed ETFNetwork=VGG13, Epochs=2002024.11———79.53
Implicit ETFNetwork=ResNet50, Epochs=502024.11———57.56
Implicit ETFNetwork=ResNet50, Epochs=2002024.11———62.75
Implicit ETFNetwork=VGG13, Epochs=502024.11———68.78
Implicit ETFNetwork=VGG13, Epochs=2002024.11———79.94
StandardNetwork=ResNet50, Epochs=502024.11———55.41
StandardNetwork=ResNet50, Epochs=2002024.11———63.6
StandardNetwork=VGG13, Epochs=502024.11———66.09
StandardNetwork=VGG13, Epochs=2002024.11———81.61