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Accurate skin lesion segmentation (SLS) plays an essential role in the computer‐aided diagnosis of skin diseases, for example, melanomas. However, the automated SLS is challenging due to variations in the nature of skin diseases, particularly the ambiguities of boundaries of skin lesion areas (SLAs) and occlusions by hairs. Though many deep learning models, represented by UNet, have been successfully...