This document discusses classifying skin lesions using artificial neural networks. It presents a dataset of 10,000 skin lesion images across 7 classes, with basal cell carcinoma and melanoma being the most dangerous types. The dataset is highly unbalanced, and the document explores two approaches to address the unbalanced data.

1. CLASSIFYING SKIN LESIONS
WITH ARTIFICIAL NEURAL
NETWORKS

2. SUMMARY
Introduction and
Literature Review
Dataset
Models
Results

4. Dataset
Total 10.000 images
• Seven Classes
• Most dangerous types of lesion are Basal Cell Carcinoma and Melanoma
• Highly unbalanced dataset
• Two approaches to fix unbalance data
INTRODUCTION AND
LITERATURE REVIEW