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Big-Volume SliceGAN for Improving a Synthetic 3D Microstructure Image of Additive-Manufactured TYPE 316L Steel
- Source :
- Journal of Imaging, Vol 9, Iss 5, p 90 (2023)
- Publication Year :
- 2023
- Publisher :
- MDPI AG, 2023.
-
Abstract
- A modified SliceGAN architecture was proposed to generate a high-quality synthetic three-dimensional (3D) microstructure image of TYPE 316L material manufactured through additive methods. The quality of the resulting 3D image was evaluated using an auto-correlation function, and it was discovered that maintaining a high resolution while doubling the training image size was crucial in creating a more realistic synthetic 3D image. To meet this requirement, modified 3D image generator and critic architecture was developed within the SliceGAN framework.
Details
- Language :
- English
- ISSN :
- 2313433X
- Volume :
- 9
- Issue :
- 5
- Database :
- Directory of Open Access Journals
- Journal :
- Journal of Imaging
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.67de21008e4d248fa0c467dca30d0c
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/jimaging9050090