Work

A Dense CNN approach for skin lesion classification

Year: 2018

Type: preprint

Abstract: 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.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.1807.06416

Authors: Carcagnì, Pierluigi, Cuna, Andrea, Distante, Cosimo

Language: English

Topic: Cutaneous Melanoma Detection and Management

Subfield: Oncology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W2884140236

Cites: 3

Cited by: 4

Related to: 10