Research on multi-apparent defects detection of concrete bridges based on YOLOR
Author:
Funder
National Natural Science Foundation of China
Publisher
Elsevier BV
Reference34 articles.
1. Experimental investigation on long-term behavior of prestressed concrete beams under coupled effect of sustained load and corrosion;Yang;Adv Struct Eng,2020
2. Using machine learning approaches to perform defect detection of existing bridges;Ruggieri;Procedia Struct Integr,2023
3. Bridge related damage quantification using unmanned aerial vehicle imagery: damage Quantification Using Unmanned Aerial Vehicle Imagery;Ellenberg;Struct Control Health Monit,2016
4. Comparison of deep convolutional neural networks and edge detectors for image-based crack detection in concrete;Dorafshan;Constr Build Mater,2018
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1. Efficacy Evaluation of You Only Learn One Representation (YOLOR) Algorithm in Detecting, Tracking, and Counting Vehicular Traffic in Real-World Scenarios, the Case of Morelia México: An Artificial Intelligence Approach;AI;2024-09-04
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