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Image Classification research benchmarks – Page 48 · SOTA2 Research

Image Classification

Benchmarks

Dataset NameSOTA MethodSort

Dataset NameSOTA methodMetricTrendResultsLast Updated

OrganCMNIST MedMNIST (test)

96.02Accuracy

33

Apr 3, 2026

CIFAR-100-C (test)

36.64Error Rate (%)

33

Jul 7, 2026

Oxford-IIIT Pets

94.1Accuracy

33

May 1, 2026

94.5Accuracy

33

Feb 27, 2026

ImageNet 1K (val)

84.3Accuracy

33

Feb 26, 2026

97.2Accuracy

33

Mar 10, 2026

EMNIST Letters 4 (test)

67.42Accuracy

33

Feb 26, 2026

Original MNIST 17 (test)

93.11Accuracy

33

Feb 26, 2026

ImageCLEF (test)

80.9Accuracy

33

Feb 26, 2026

79.9Accuracy (20% Symmetric Noise)

33

Feb 26, 2026

98Top-1 Acc

33

Feb 26, 2026

iNaturalist 2018 (All)

RIDE (6 experts)

74.6Top-1 Accuracy

33

Feb 27, 2026

CIFAR-10 (test)

150Targeted Communication Cost

33

Feb 26, 2026

CIFAR-10 non-IID s=2

91.82Test Accuracy

33

May 29, 2026

WebVision 50 (val)

79.96Top-1 Acc

33

Feb 26, 2026

81.1Accuracy

33

Feb 26, 2026

ImageNet 1% labels 1.0 (val)

59.9Top-1 Acc

33

Feb 26, 2026

CompCars Web (test)

95.9Top-1 Acc

33

Feb 26, 2026

S-CIFAR-10 Task-IL

98.31Accuracy

33

Feb 26, 2026

Zero-Shot baseline

98Accuracy

33

Feb 26, 2026

CIFAR-100 Sym-20% (test)

75.79Accuracy

33

Feb 26, 2026

94.33Accuracy (Pruned)

33

Feb 26, 2026

CIFAR-10 Asymmetric Noise (test)

95.5Accuracy (40% Noise)

33

Feb 26, 2026

SVHN to MNIST standard (test)

99.61Accuracy

33

Feb 26, 2026

ILSVRC 2015 (val)

Learning like a Child

76.71Top-1 Acc (C_large)

33

Feb 26, 2026

Page 48 of 333

Popular datasets

CIFAR ImageNet MNIST CIFAR-10 CIFAR-100

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