# Ensemble of Convolutional Neural Networks for Dermoscopic Images Classification

arXiv: https://arxiv.org/abs/1808.05071 · HTML: https://mlsanity.com/paper/1808.05071/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Aug 2018.

## Built on by (most cited first, 2 of 2)

- [Self-supervised learning for skin cancer diagnosis with limited training data](https://mlsanity.com/paper/2401.00692/) (2024)
- [Skin Lesion Diagnosis Using Convolutional Neural Networks](https://mlsanity.com/paper/2305.11125/) (2023)

## Abstract (arXiv)

In this report, we are presenting our automated prediction system for disease classification within dermoscopic images. The proposed solution is based on deep learning, where we employed transfer learning strategy on VGG16 and GoogLeNet architectures. The key feature of our solution is preprocessing based primarily on image augmentation and colour normalization. The solution was evaluated on Task 3: Lesion Diagnosis of the ISIC 2018: Skin Lesion Analysis Towards Melanoma Detection.