Self-supervised multi-task representation learning for sequential medical images
Self-supervised representation learning has achieved promising results for downstream visual tasks in natural images. However, its use in the medical domain, where there is an underlying anatomical structural similarity, remains underexplored. To address this shortcoming, we propose a self-supervise...
| 主要な著者: | , , |
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| フォーマット: | Conference item |
| 言語: | English |
| 出版事項: |
Springer
2021
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