Tuning-Free Incremental Learning via Multilevel Prototypical Parts for Few-Shot Land Cover Segmentation
Dynamic Earth observation applications often require land-cover segmentation models to recognize newly emerging classes from only a few pixel-level annotations while retaining previously learned knowledge. However, gradient-based incremental fine-tuning (FT) is prone to severe overfitting and catastrophic forgetting un...