Label-Efficient Self-Supervised Federated Learning for Tackling Data Heterogeneity in Medical Imaging
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on medical imaging"
DOI: 10.1109/tmi.2022.3233574
Abstract: The collection and curation of large-scale medical datasets from multiple institutions is essential for training accurate deep learning models, but privacy concerns often hinder data sharing. Federated learning (FL) is a promising solution that enables… read more here.
Keywords: data heterogeneity; federated learning; self supervised; medical imaging ... See more keywords
A Survey on Label-efficient Deep Segmentation: Bridging the Gap between Weak Supervision and Dense Prediction
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on pattern analysis and machine intelligence"
DOI: 10.48550/arxiv.2207.01223
Abstract: The rapid development of deep learning has made a great progress in image segmentation, one of the fundamental tasks of computer vision. However, the current segmentation algorithms mostly rely on the availability of pixel-level annotations,… read more here.
Keywords: image segmentation; supervision; segmentation; efficient deep ... See more keywords