The accurate detection of lesion attributes is meaningful for both the computeraid diagnosis
system and dermatologists decisions. However, unlike lesion segmentation and melenoma
classification, there are few deep learning methods and literatures focusing on this task.
Currently, the lesion attribute detection still remains challenging due to the extremely
unbalanced class distribution and insufficient samples, as well as large intraclass and low
interclass variations. To solve these problems, we propose a deep learning framework …