Vision transformer for skin cancer classification

Abstract

This paper investigates the use of vision transformers (ViT) for skin cancer classification tasks, compared to convolutional models. We propose a novel ViT architecture that effectively classifies skin cancer images. Our findings suggest that ViT models have the potential to outperform convolutional models, especially with larger datasets.