High Resolution X-Ray CT Reconstruction of Additively Manufactured Metal Parts using Generative Adversarial Network-based Domain Adaptation in AI-CT-Reference-Cited by-同舟云学术

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High Resolution X-Ray CT Reconstruction of Additively Manufactured Metal Parts using Generative Adversarial Network-based Domain Adaptation in AI-CT

Published:2021-07-30 Issue:S1 Volume:27 Page:2940-2942
ISSN:1431-9276
Container-title:Microscopy and Microanalysis
language:en
Short-container-title:Microsc Microanal

Author:

Ziabari Amir,Dubey Abhishek,Venkatakrishnan Singanallur,Frederick Curtis,Bingham Philip,Dehoff Ryan,Paquit Vincent

Publisher

Cambridge University Press (CUP)

Subject

Instrumentation

Reference8 articles.

1. Deep residual learning enabled metal artifact reduction in CT;Xu;in SPIE Medical Imaging,2018

2. A Survey of Unsupervised Deep Domain Adaptation

3. A Model-Based Image Reconstruction Algorithm With Simultaneous Beam Hardening Correction for X-Ray CT

4. Beam Hardening Artifact Reduction in X-Ray CT Reconstruction of 3D Printed Metal Parts Leveraging Deep Learning and CAD Models

5. An energy-based beam hardening model in tomography

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Data-Driven Framework for Direct Local Tensile Property Prediction of Laser Powder Bed Fusion Parts;Materials;2023-11-23

2. Scalable in situ non-destructive evaluation of additively manufactured components using process monitoring, sensor fusion, and machine learning;Additive Manufacturing;2023-09

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