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Found 2 papers, 1 papers with code
An Evaluation of Non-Contrastive Self-Supervised Learning for Federated Medical Image Analysis
In this paper, we seek to tackle these concerns head-on and systematically explore the applicability of non-contrastive self-supervised learning (SSL) algorithms under federated learning (FL) simulations for medical image analysis.
Exploring Self-Supervised Representation Learning For Low-Resource Medical Image Analysis
The success of self-supervised learning (SSL) has mostly been attributed to the availability of unlabeled yet large-scale datasets.
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