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Resource-efficient domain adaptive pre-training for medical images
[article]
2022
arXiv
pre-print
The deep learning-based analysis of medical images suffers from data scarcity because of high annotation costs and privacy concerns. Researchers in this domain have used transfer learning to avoid overfitting when using complex architectures. However, the domain differences between pre-training and downstream data hamper the performance of the downstream task. Some recent studies have successfully used domain-adaptive pre-training (DAPT) to address this issue. In DAPT, models are initialized
arXiv:2204.13280v1
fatcat:ubul5k7b5rfwrhopepzwhtqt7y