PatchNR: learning from very few images by patch normalizing flow regularization
Learning neural networks using only few available information is an important ongoing research topic with tremendous potential for applications. In this paper, we introduce a powerful regularizer for the variational modeling of inverse problems in imaging. Our regularizer, called patch normalizing f...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Institute of Physics
2023
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| Subjects: | |
| Online Access: | View Fulltext in Publisher View in Scopus |