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Image Classification research benchmarks – Page 243 · SOTA2 Research

Image Classification

Benchmarks

Dataset NameSOTA MethodSort

Dataset NameSOTA methodMetricTrendResultsLast Updated

SNN-SqueezeNet-P

45Accuracy

6

Feb 26, 2026

SNN-SqueezeNet-P

54Acc

6

Feb 26, 2026

CIFAR-10 L-2 norm, epsilon=0.5 (test)

95.74Accuracy (Standard)

6

Feb 26, 2026

89Accuracy

6

Feb 26, 2026

89.74Accuracy

6

Feb 26, 2026

CIFAR-10 standard

81.08Accuracy

6

Feb 26, 2026

82.05Mean Accuracy

6

Feb 26, 2026

93.8Accuracy

6

Feb 26, 2026

77Accuracy

6

Feb 26, 2026

52Accuracy

6

Feb 26, 2026

63Accuracy

6

Feb 26, 2026

Food101 (10% labels)

Meta Co-Training

94.8Top-1 Accuracy

6

Feb 26, 2026

SVHN standard (test)

93.37Clean Accuracy

6

Feb 26, 2026

ImageNet-1K and Variants (V2, A, R, O, Sketch) 1.0 (test)

38.6ImageNet-1K Accuracy

6

Feb 26, 2026

DomainNet Clipart 10-shot (test)

71.13Accuracy

6

Feb 26, 2026

Places365 10-shot (test)

39.46Accuracy

6

Feb 26, 2026

Places365 5-shot (test)

35.31Accuracy

6

Feb 26, 2026

D.Net-Cl 10-shot (test)

72.92Accuracy

6

Feb 26, 2026

D.Net-Cl 5-shot (test)

66.13Accuracy

6

Feb 26, 2026

D.Net-Cl 3-shot (test)

59.83Accuracy

6

Feb 26, 2026

D.Net-Cl 10-shot

58.27Accuracy

6

Feb 26, 2026

CIFAR-100 10-shot

68.9Accuracy

6

Feb 26, 2026

D.Net-Cl 5-shot

46.64Accuracy

6

Feb 26, 2026

CIFAR-100 5-shot

58.22Accuracy

6

Feb 26, 2026

D.Net-Cl 3-shot

34.65Accuracy

6

Feb 26, 2026

Page 243 of 333

Popular datasets

CIFAR ImageNet MNIST CIFAR-10 CIFAR-100

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