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Papers Benchmarks Datasets Tasks

HAM10000 dataset and benchmarks – Page 3 · SOTA2 Research

Research Datasets

HAM10000

Benchmarks

Task NameDataset NameSOTA MethodSort

Task NameDataset NameSOTA ResultTrendResults

HAM10000

84.48Mean Accuracy

6

Image Synthesis

HAM10000 v1 (test)

51.56FID

6

Learning to Defer

HAM10000 OOD

86SAC

6

Image Segmentation

HAM10000 47 (test)

78.8mIoU

5

Membership Inference Attack

HAM10000 (lesion-level splitting)

80.6MIA Accuracy

4

Dermoscopy Visual Question Answering

HAM10000

19.56Gender Accuracy (ES)

4

Skin Lesion Classification

HAM10000 1,000-image subset 1.0

78.5Accuracy

4

Explanation Generation

HAM10000

1EE

4

Fine-grained Image Classification

HAM10000

79.37Accuracy

4

Concept Faithfulness

HAM10000 (val)

100Accuracy

3

Uncertainty Estimation Alignment

HAM10000 100 expert re-annotated images

0.691Kappa

3

Medical Image Segmentation

HAM10000 100 expert re-annotated images

73.91IoU (con)

3

Skin Lesion Classification

HAM10000

0.18Energy (J/sample) Lite

3

Identification of skin lesions

HAM10000

85Accuracy (%)

3

Concept Coverage Estimation

HAM10000

57Concept Coverage

2

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Popular tasks

Classification Skin lesion classification Image Classification Medical Image Classification Skin Lesion Segmentation

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