An improved transformer network for skin cancer classification

•An improved vision transformer-based model for skin cancer classification is proposed.•Multi-scale and overlapping sliding windows, and multi-scale patch embedding is carried out.•The contrastive learning method for skin cancer classification is applied.•Label shuffling for a balanced sampling of skin cancer datasets is applied.•Our proposed model is evaluated on two skin cancer datasets and achieved promising results.