Unsupervised Domain Adaptation Network With Category-Centric Prototype Aligner for Biomedical Image Segmentation
With the widespread success of deep learning in biomedical image segmentation, domain shift becomes a critical and challenging problem, as the gap between two domains can severely affect model performance when deployed to unseen data with heterogeneous features. To alleviate this problem, we present...
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| Main Authors: | , , , , |
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| Format: | article |
| Language: | EN |
| Published: |
IEEE
2021
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| Subjects: | |
| Online Access: | https://doaj.org/article/e246d9dba5aa49b89dd40c7392e666f7 |
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