Enhanced Skin Cancer Classification Using Deep Learning and Gradient Boosting Techniques

Overview

This conference paper explores a skin-cancer classification pipeline that combines deep-learning image features with gradient-boosting techniques. The approach aims to use representations learned by neural networks while drawing on the practical strengths of boosted decision trees. It evaluates this combination for distinguishing skin-cancer categories and contributes to research on computer-assisted analysis of medical images.