MedMerge: Merging Models for Effective Transfer Learning to Medical Imaging Tasks

arXiv:2403.11646v1 Announce Type: new
Abstract: Transfer learning has become a powerful tool to initialize deep learning models to achieve faster convergence and higher performance. This is especially useful in the medical imaging analysis domain, where data scarcity limits possible performance gains for deep learning models. Some advancements have been made in boosting the transfer learning performance gain by merging models starting from the same initialization. However, in the medical imaging analysis domain, there is an opportunity in merging models starting …

abstract analysis arxiv become convergence cs.cv data deep learning domain faster imaging medical medical imaging merging performance tasks tool transfer transfer learning type