# Image Classification of Melanoma, Nevus and Seborrheic Keratosis by Deep Neural Network Ensemble

Source: [Image Classification of Melanoma, Nevus and Seborrheic Keratosis by Deep Neural Network Ensemble](<https://www.sota2.com/research/paper/68fa63361e209131ce9fd74c>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-27T05:52:51.467Z

Authors: Kazuhisa Matsunaga, Akira Hamada, Akane Minagawa, Hiroshi Koga

Published: 2017-03-09T02:35:59.000Z

## Abstract

This short paper reports the method and the evaluation results of Casio and Shinshu University joint team for the ISBI Challenge 2017 - Skin Lesion Analysis Towards Melanoma Detection - Part 3: Lesion Classification hosted by ISIC. Our online validation score was 0.958 with melanoma classifier AUC 0.924 and seborrheic keratosis classifier AUC 0.993.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1703.03108>)

[PDF](<https://arxiv.org/pdf/1703.03108.pdf>)