Feature-level rectified flow generation plus dual-layer knowledge distillation yields a one-shot federated learning method that beats several baselines on three non-IID medical imaging datasets.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
A New One-Shot Federated Learning Framework for Medical Imaging Classification with Feature-Guided Rectified Flow and Knowledge Distillation
Feature-level rectified flow generation plus dual-layer knowledge distillation yields a one-shot federated learning method that beats several baselines on three non-IID medical imaging datasets.