Deep Learning Unlocks X‐ray Microtomography Segmentation of Multiclass Microdamage in Heterogeneous Materials-Reference-Cited by-同舟云学术

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Deep Learning Unlocks X‐ray Microtomography Segmentation of Multiclass Microdamage in Heterogeneous Materials

Published:2021-11-20 Issue: Volume: Page:2107817
ISSN:0935-9648
Container-title:Advanced Materials
language:en
Short-container-title:Adv. Mater.

Author:

Kopp Reed¹,Joseph Joshua²,Ni Xinchen¹,Roy Nicholas¹²,Wardle Brian L.¹³

Affiliation:

1. Department of Aeronautics and Astronautics Massachusetts Institute of Technology 77 Massachusetts Avenue Cambridge MA 02139 USA

2. MIT Quest for Intelligence Massachusetts Institute of Technology 77 Massachusetts Avenue Cambridge MA 02139 USA

3. Department of Mechanical Engineering Massachusetts Institute of Technology 77 Massachusetts Avenue Cambridge MA 02139 USA

Publisher

Wiley

Subject

Mechanical Engineering,Mechanics of Materials,General Materials Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/adma.202107817

Cited by 9 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. In situ X-ray imaging and numerical modeling of damage accumulation in C/SiC composites at temperatures up to 1200 °C;Journal of Materials Science & Technology;2024-10

2. Hygrothermal progressive damage in open-hole compression of composite laminates with aligned carbon nanotube interlaminar reinforcement studied by X-ray micro-computed tomography;Composites Part B: Engineering;2024-06

3. Hyperparameter tuning for deep learning semantic image segmentation of micro computed tomography scanned fiber-reinforced composites;Tomography of Materials and Structures;2024-06

4. A Semiautomated Modular Approach for Multiscale In-Situ Effective Mechanical Property Prediction from Computed Tomography of As-Built Composites;AIAA SCITECH 2024 Forum;2024-01-04

5. Towards full-stack deep learning-empowered data processing pipeline for synchrotron tomography experiments;The Innovation;2024-01

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