Deep convolutional neural network ensemble for pavement crack detection using high elevation UAV images-Reference-Cited by-同舟云学术

Deep convolutional neural network ensemble for pavement crack detection using high elevation UAV images

Published:2023-10-02 Issue: Volume: Page:1-16
ISSN:1573-2479
Container-title:Structure and Infrastructure Engineering
language:en
Short-container-title:Structure and Infrastructure Engineering

Author:

Amieghemen Goodnews E.¹^ORCID,Sherif Muhammad M.¹^ORCID

Affiliation:

1. Department of Civil, Construction, and Environmental Engineering, School of Engineering, University of Alabama at Birmingham, AL, USA

Publisher

Informa UK Limited

Subject

Mechanical Engineering,Ocean Engineering,Geotechnical Engineering and Engineering Geology,Safety, Risk, Reliability and Quality,Building and Construction,Civil and Structural Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/15732479.2023.2263441

Reference52 articles.

1. Robust Pixel-Level Crack Detection Using Deep Fully Convolutional Neural Networks

2. Deep Learning-Based Crack Damage Detection Using Convolutional Neural Networks

3. Chen L. C. Zhu Y. Papandreou G. Schroff F. & Adam H. (2018). Encoder-decoder with atrous separable convolution for semantic image segmentation. In Proceedings of the European Conference on Computer Vision (ECCV) (pp. 801–818).

4. Pavement crack detection using hessian structure propagation

5. Anomaly detection of defects on concrete structures with the convolutional autoencoder

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