Image classification for sub-surface crack identification in concrete dam based on borehole CCTV images using deep dense hybrid model-Reference-Cited by-同舟云学术

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Image classification for sub-surface crack identification in concrete dam based on borehole CCTV images using deep dense hybrid model

Published:2024-07-08 Issue: Volume: Page:
ISSN:1436-3240
Container-title:Stochastic Environmental Research and Risk Assessment
language:en
Short-container-title:Stoch Environ Res Risk Assess

Author:

Dai Qianwei,Ishfaque Muhammad,Khan Saif Ur Rehman,Luo Yu-Long,Lei Yi,Zhang Bin,Zhou Wei

Funder

National Natural Science Foundation of China

Postdoctoral Science Foundation of Central South University

National Key Research and Development Program of China

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s00477-024-02743-x.pdf

Reference52 articles.

1. Ahmed MF, Sher F, Mehmood E (2023) Evaluation of landslide hazards potential at Dasu dam site and its reservoir area. Environ Earth Sci 82(7):183

2. Atila Ü et al (2021) Plant leaf disease classification using EfficientNet deep learning model. Eco Inform 61:101182

3. Bae H, An Y-K (2023) Computer vision-based statistical crack quantification for concrete structures. Measurement 211:112632

4. Bonaccorso G (2017) Machine learning algorithms. Packt Publishing Ltd

5. Boulange J et al (2021) Role of dams in reducing global flood exposure under climate change. Nat Commun 12(1):417

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