Attention-Based Biomedical Image Classification: Enhancing Locality and Generalization

Attention-based models can effectively replace computationally complex convolutional neural networks (CNNs) for biomedical image analysis by capturing long-range dependencies and introducing locality through novel techniques like Shifted Patch Tokenization (S.P.T.) and Lancoz5 interpolation.