Improvement of Fine Structure Preservation in Denoising by Self-Supervised Learning Compared to Supervised Learning
Inline computed tomography (CT) enables rapid quality control but suffers from high noise due to short scan times. While deep learning offers powerful denoising capabilities, standard supervised models require clean reference data which is often unavailable in industrial settings and which tend to...
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| Główni autorzy: | , , , , , , , , |
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| Format: | Artigo |
| Język: | Alemão |
| Wydane: |
NDT.net
2026-03-01
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| Seria: | e-Journal of Nondestructive Testing |
| Dostęp online: | https://www.ndt.net/search/docs.php3?id=32565 |
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