Automated Concrete Crack Inspection With Directional Lighting Platform
Author:
Affiliation:
1. Department of Civil, Environmental Engineering, University of Strathclyde, Glasgow, U.K.
2. Department of Electronic, Electrical Engineering, University of Strathclyde, Glasgow, U.K.
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Instrumentation
Link
http://xplorestaging.ieee.org/ielx7/7782634/10274874/10295569.pdf?arnumber=10295569
Reference15 articles.
1. Threshold-Based BRISQUE-Assisted Deep Learning for Enhancing Crack Detection in Concrete Structures
2. Crack Detection of Concrete Pavement With Cross-Entropy Loss Function and Improved VGG16 Network Model
3. Comparison of deep convolutional neural networks and edge detectors for image-based crack detection in concrete
4. Skeleton-based noise removal algorithm for binary concrete crack image segmentation
5. Performance comparison of pretrained convolutional neural networks on crack detection in buildings;ozgenel;Robotics and Automation in Construction,2019
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