What is Wrong with Continual Learning in Medical Image Segmentation?
UNEG, a multi-model benchmark for continual learning in medical image segmentation, outperforms existing methods by maintaining separate networks for each training stage and using reconstruction error to select the appropriate model during inference, highlighting the importance of robust baselines over catastrophic forgetting prevention.
Feb 10, 2023
