A Modular U-Net for Automated Segmentation of X-Ray Tomography Images in Composite Materials

A Modular U-Net for Automated Segmentation of X-Ray Tomography Images in Composite Materials

X-Ray Computed Tomography (XCT) techniques have evolved to a point that high-resolution data can be acquired so fast that classic segmentation methods are prohibitively cumbersome, demanding automated data pipelines capable of dealing with non-trivial 3D images. Meanwhile, deep learning has demonstr...

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Bibliographic Details
Main Authors: João P. C. Bertoldo, Etienne Decencière , David Ryckelynck , Henry Proudhon
Format: article
Language:EN
Published: Frontiers Media S.A. 2021
Subjects:
deep learning
U-net
modular network architecture
semantic segmentation
3D X-ray computed tomography (XCT)
composite material
Technology
T
Online Access:https://doaj.org/article/679dbf87b1ff4732838daf11f3be2271
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https://doaj.org/article/679dbf87b1ff4732838daf11f3be2271

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