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Automatic Crack Detection Using Weakly Supervised Semantic Segmentation Network and Mixed-Label Training Strategy Cover

Automatic Crack Detection Using Weakly Supervised Semantic Segmentation Network and Mixed-Label Training Strategy

Foundations of Computing and Decision Sciences
Volume 49 (2024): Issue 1 (February 2024)
By: Shuyuan Zhang,  Hongli Xu,  Xiaoran Zhu and  Lipeng Xie  
Open Access
|Feb 2024

Authors

Shuyuan Zhang

School of Cyber Science and Engineering, Zhengzhou University, Zhengzhou, China

Hongli Xu

School of Cyber Science and Engineering, Zhengzhou University, Zhengzhou, China

Xiaoran Zhu

Hanwei Electronics Group Corporation, Zhengzhou, China

Lipeng Xie

Hanwei Electronics Group Corporation, Zhengzhou, China
DOI: https://doi.org/10.2478/fcds-2024-0007 | Journal eISSN: 2300-3405 | Journal ISSN: 0867-6356
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Language: English
Page range: 95 - 118
Submitted on: Aug 30, 2023
Accepted on: Nov 16, 2023
Published on: Feb 16, 2024
Published by: Poznan University of Technology
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
weakly supervised learning,
crack detection,
semantic segmentation,
mixed label
Related subjects:
Computer sciences,
Artificial intelligence,
Software development

© 2024 Shuyuan Zhang, Hongli Xu, Xiaoran Zhu, Lipeng Xie, published by Poznan University of Technology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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