Segmentation of pores in carbon fiber reinforced polymers using the U-Net convolutional neural network

Segmentation of pores in carbon fiber reinforced polymers using the U-Net convolutional neural network

This study demonstrates the utilization of deep learning techniques for binary semantic segmentation of pores in carbon fiber reinforced polymers (CFRP) using X-ray computed tomography (XCT) datasets. The proposed workflow is designed to generate efficient segmentation models with reasonable execut...

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Bibliographic Details
Main Authors: Miroslav Yosifov, Patrick Weinberger, Bernhard Plank, Bernhard Fröhler, Markus Hoeglinger, Johann Kastner, Christoph Heinzl
Format: Article
Language:English
Published: Czech Technical University in Prague 2023-10-01
Series:Acta Polytechnica CTU Proceedings
Subjects:
deep learning
segmentation
U-Net
computed tomography
pores
carbon fiber reinforced polymers
Online Access:https://ojs.cvut.cz/ojs/index.php/APP/article/view/9407
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