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CrackNet-VGG: A Deep Learning Framework for Automated Detection of Surface Cracks in Concrete Structures Cover

CrackNet-VGG: A Deep Learning Framework for Automated Detection of Surface Cracks in Concrete Structures

Applied Computer Systems
Volume 30 (2025): Issue 1 (January 2025)
By: Saiqa Murtaza,  Muhammad Imran and  Muhammad Rizwan Rashid Rana  
Open Access
|Dec 2025
DOI: https://doi.org/10.2478/acss-2025-0020 | Journal eISSN: 2255-8691 | Journal ISSN: 2255-8683
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Language: English
Page range: 187 - 194
Submitted on: Jul 28, 2025
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Accepted on: Nov 27, 2025
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Published on: Dec 23, 2025
Published by: Riga Technical University
In partnership with: Paradigm Publishing Services
Publication frequency: Volume open
Keywords:
Concrete crack detection,
convolutional neural network,
deep learning,
structural health monitoring,
VGG16 architecture
Related subjects:
Computer sciences,
Artificial intelligence,
Information technology,
Project management,
Software development

© 2025 Saiqa Murtaza, Muhammad Imran, Muhammad Rizwan Rashid Rana, published by Riga Technical University
This work is licensed under the Creative Commons Attribution 4.0 License.

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