Machine learning based approach for surface roughness prediction in precision dental prototyping
Abstract Complex geometries achievable with resin-based 3D printing are susceptible to lower levels of surface roughness, particularly in areas where support structures are attached and removed. The slicing parameter serves as the cornerstone for developing a model for predicting the corresponding o...
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| Autori principali: | , , , , , , , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Nature Portfolio
2025-09-01
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| Serie: | Scientific Reports |
| Soggetti: | |
| Accesso online: | https://doi.org/10.1038/s41598-025-17487-z |
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