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. Author manuscript; available in PMC: 2024 Jul 1.
Published in final edited form as: IEEE Trans Med Imaging. 2023 Jun 30;42(7):1932–1943. doi: 10.1109/TMI.2022.3233574

TABLE VI:

Test accuracy (%) for federated fine-tuning on the Retina dataset using the proposed methods and federated self-supervised pre-training baselines.

Method Backbone Central Split1 Split2 Split3
Rand. init. ViT-B 73.70 74.33 69.50 64.13
FedMoCov3 ViT-B 79.35 78.06 74.98 72.32
FedMoCo ResNet-50 77.50 75.80 73.03 70.10
FedBYOL ResNet-50 80.10 78.43 75.27 72.93
FedEMA [27] ResNet-50 80.12 78.51 76.08 73.96
Fed-BEiT ViT-B 79.47 78.40 76.80 76.77
Fed-MAE ViT-B 81.93 81.67 79.40 77.43