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Transfer Learning in Medical Image Segmentation: New Insights from Analysis of the Dynamics of Model Parameters and Learned Representations
We present a critical assessment of the role of transfer learning in training fully convolutional networks (FCNs) for medical image segmentation. We first show that although transfer learning reduces the training time on the target task, improvements in segmentation accuracy are highly task/data-dep...
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| Publié dans: | Artif Intell Med |
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| Auteurs principaux: | , , |
| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
2021
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| Sujets: | |
| Accès en ligne: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8164174/ https://ncbi.nlm.nih.gov/pubmed/34020754 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.artmed.2021.102078 |
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