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Generalisable 3D printing error detection and correction via multi-head neural networks
Material extrusion is the most widespread additive manufacturing method but its application in end-use products is limited by vulnerability to errors. Humans can detect errors but cannot provide continuous monitoring or real-time correction. Existing automated approaches are not generalisable across...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Nature Publishing Group UK
2022
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9378646/ https://www.ncbi.nlm.nih.gov/pubmed/35970824 http://dx.doi.org/10.1038/s41467-022-31985-y |