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Semi-supervised Image Classification on Flowers 10% (train)

98.18Accuracy

GRaNDe

Updated 8d ago

Evaluation Results

Method	Links
GRaNDe 2026.05		98.18
DGCG 2026.05		98.09
WSEF 2026.05		97.82
MGCN 2026.05		97.43
PL+ SGD 2026.05		96.84
SVM 2026.05		96.75
GNN-LDS 2026.05		96.66
OPF 2026.05		96.5
LS+ kNN 2026.05		95.74
LS+ ML-Perc. 2026.05		95.13
LS+ SVM 2026.05		94.49
LS+ OPF 2026.05		94.22
ML-Perc. 2026.05		92.59
GRaNDe 2026.05		86.19
MGCN 2026.05		85.88
DGCG 2026.05		85.68
WSEF 2026.05		85.12
PL+ SGD 2026.05		82.69
CoMatch 2026.05		82.55
SVM 2026.05		80.54
GRaNDe 2026.05		80.1
GNN-LDS 2026.05		79.32
ML-Perc. 2026.05		78.88
MGCN 2026.05		78.82
DGCG 2026.05		78.42
PL+ SGD 2026.05		76.87
WSEF 2026.05		76.16
GNN-LDS 2026.05		73.69
LS+ SVM 2026.05		73.53
LS+ kNN 2026.05		73.49
SVM 2026.05		73.3
LS+ ML-Perc. 2026.05		73.03
LS+ OPF 2026.05		72.66
ML-Perc. 2026.05		72.62
OPF 2026.05		71.77
OPF 2026.05		64
LS+ SVM 2026.05		59.84
LS+ ML-Perc. 2026.05		59.39
LS+ OPF 2026.05		59.25
LS+ kNN 2026.05		58.05