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The Application of Convolutional Neural Networks (CNNs) to Recognize Defects in 3D-Printed Parts
Cracks and pores are two common defects in metallic additive manufacturing (AM) parts. In this paper, deep learning-based image analysis is performed for defect (cracks and pores) classification/detection based on SEM images of metallic AM parts. Three different levels of complexities, namely, defec...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8156518/ https://www.ncbi.nlm.nih.gov/pubmed/34063484 http://dx.doi.org/10.3390/ma14102575 |