This paper examines combining few-shot learning and transfer learning to address challenges in classifying rare skin diseases with limited data. Models using DenseNet121, MobileNetV2, ImageNet pretraining, episodic training, and data augmentation are tested on datasets like SD-198. Key findings show transfer learning helps represent features and boosts performance, trad...