This article presents a Deep CNN, based on the DenseNet architecture jointly with a highly discriminating learning methodology, in order to classify seven kinds of skin lesions: Melanoma, Melanocytic nevus, Basal cell carcinoma, Actinic keratosis / Bowen's disease, Benign keratosis, Dermatofibroma, Vascular lesion. In particular a 61 layers DenseNet, pre-trained on IMAGENET dataset, has been fine-tuned on ISIC 2018 Task 3 Challenge Dataset exploiting a Center Loss function.
@article{arxiv.1807.06416,
title = {A Dense CNN approach for skin lesion classification},
author = {Pierluigi Carcagnì and Andrea Cuna and Cosimo Distante},
journal= {arXiv preprint arXiv:1807.06416},
year = {2018}
}