Skin Cancer Classification
14 papers with code • 1 benchmarks • 1 datasets
ISIC 2020 Challenge Dataset
Most implemented papers
Skin Deep Unlearning: Artefact and Instrument Debiasing in the Context of Melanoma Classification
pbevan1/Skin-Deep-Unlearning
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Convolutional Neural Networks have demonstrated dermatologist-level performance in the classification of melanoma from skin lesion images, but prediction irregularities due to biases seen within the training data are an issue that should be addressed before widespread deployment is possible.
Leveraging Contextual Data Augmentation for Generalizable Melanoma Detection
This paper challenges this notion and argues that mole size, a critical attribute in professional dermatology, can be misleading in automated melanoma detection.
SkinDistilViT: Lightweight Vision Transformer for Skin Lesion Classification
longman-stan/skindistilvit
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By adding classification heads at each level of the transformer and employing a cascading distillation process, we improve the balanced multi-class accuracy of the base model by 2. 1%, while creating a range of models of various sizes but comparable performance.
Revisiting Skin Tone Fairness in Dermatological Lesion Classification
tkalbl/revisitingskintonefairness
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Addressing fairness in lesion classification from dermatological images is crucial due to variations in how skin diseases manifest across skin tones.
