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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...

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Detalles Bibliográficos
Autores principales:	Wen, Hao, Huang, Chang, Guo, Shengmin
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2021
Materias:	Article
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

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