On a new 51-class dataset of everyday skin photos, the Swin Transformer outperforms eight CNN and transformer baselines, reaching about 81 percent accuracy.
The global burden of skin disease in 2010: An analysis of the prevalence and impact of skin conditions,
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Toward Accessible Dermatology: Skin Lesion Classification Using Deep Learning Models on Mobile-Acquired Images
On a new 51-class dataset of everyday skin photos, the Swin Transformer outperforms eight CNN and transformer baselines, reaching about 81 percent accuracy.