Multidamage Identification in High-Resolution Concrete Bridge Component Imagery Based on Deep Learning-Reference-Cited by-同舟云学术

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Multidamage Identification in High-Resolution Concrete Bridge Component Imagery Based on Deep Learning

Published:2024-10 Issue:5 Volume:38 Page:
ISSN:0887-3828
Container-title:Journal of Performance of Constructed Facilities
language:en
Short-container-title:J. Perform. Constr. Facil.

Author:

Tang Hai-En¹,Yi Ting-Hua²,Zhang Song-Han³,Li Chong⁴

Affiliation:

1. Master’s Student, School of Civil Engineering, Dalian Univ. of Technology, Dalian 116023, China.

2. Professor, School of Civil Engineering, Dalian Univ. of Technology, Dalian 116023, China (corresponding author).

3. Associate Professor, School of Civil Engineering, Dalian Univ. of Technology, Dalian 116023, China.

4. Senior Engineer, CCCC Highway Bridges National Engineering Research Centre Co., Ltd., No. 23 Huangsi St., Xicheng District, Beijing 100120, China.

Publisher

American Society of Civil Engineers (ASCE)

Link

https://ascelibrary.org/doi/pdf/10.1061/JPCFEV.CFENG-4671

Reference36 articles.

1. Analysis of Edge-Detection Techniques for Crack Identification in Bridges

2. Efficient Object Detection and Classification Approach Using HTYOLOV4 and M2RFO-CNN

3. Artificial intelligence and smart vision for building and construction 4.0: Machine and deep learning methods and applications

4. Automatic recognition of concrete spall using image processing and metaheuristic optimized LogitBoost classification tree

5. Autonomous Structural Visual Inspection Using Region-Based Deep Learning for Detecting Multiple Damage Types

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