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Image Classification research benchmarks – Page 163 · SOTA2 Research

Image Classification

Benchmarks

Dataset NameSOTA MethodSort

Dataset NameSOTA methodMetricTrendResultsLast Updated

MNIST non-i.i.d. (test)

93.08Accuracy

10

Feb 26, 2026

CIFAR-10 (test)

Pang et al. (2020)

86.43Clean Accuracy

10

Feb 26, 2026

EMNIST (non-iid)

84.42Accuracy

10

Feb 26, 2026

EMNIST iid (test)

85.04Test Accuracy

10

Feb 26, 2026

89.6Accuracy (Severity 0)

10

Feb 26, 2026

72.3Acc (Sev 0)

10

Feb 26, 2026

93.1Accuracy (Severity 0)

10

Feb 26, 2026

CIFAR-10 (test)

LipNeXt L32W2048

85Clean Accuracy

10

Feb 26, 2026

MNIST-C Fog (target)

79.2Avg Accuracy

10

Feb 26, 2026

Multi-domain MNIST (train)

99.47Accuracy (Clean)

10

Feb 26, 2026

Multi-domain MNIST (test)

97.24Acc (Rotated)

10

Feb 26, 2026

CIFAR-100 (test)

62.5Top-1 Accuracy

10

Feb 26, 2026

CIFAR-10 (test)

88.5Top-1 Acc

10

Feb 26, 2026

UNSW Predators (test)

95.92Accuracy

10

Feb 26, 2026

CIFAR-100 (test)

59.57Clean Accuracy

10

Feb 26, 2026

Injured vs. Uninjured soldier dataset

Patch-Driven Relational Gated Graph Attention

94.9Accuracy

10

Feb 26, 2026

32.34AutoAttack Robustness

10

Feb 27, 2026

59.01Clean Accuracy

10

Apr 1, 2026

Vanilla training

5.24Clean Error

10

Feb 26, 2026

85.32R@1

10

Feb 26, 2026

85.96Top-1 Recall

10

Feb 26, 2026

AA-Central (test)

0.923Top-1 Accuracy

10

Feb 26, 2026

91.8AUC

10

Feb 26, 2026

78.4AUC

10

Feb 26, 2026

RSNA-Pneumonia 5,337 images (test)

72.7AP

10

Feb 26, 2026

Page 163 of 333

Popular datasets

CIFAR ImageNet MNIST CIFAR-10 CIFAR-100

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