Machine Learning for Crack Detection: Review and Model Performance Comparison-Reference-Cited by-同舟云学术

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Machine Learning for Crack Detection: Review and Model Performance Comparison

Published:2020-09 Issue:5 Volume:34 Page:04020038
ISSN:0887-3801
Container-title:Journal of Computing in Civil Engineering
language:en
Short-container-title:J. Comput. Civ. Eng.

Author:

Hsieh Yung-An¹^ORCID,Tsai Yichang James²^ORCID

Affiliation:

1. Ph.D. Candidate, Dept. of Computer and Electrical Engineering, Georgia Institute of Technology, Atlanta, GA 30332 (corresponding author). ORCID: .

2. Professor, Dept. of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332. ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Computer Science Applications,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29CP.1943-5487.0000918

Reference94 articles.

1. Automatic Crack Detection on Two-Dimensional Pavement Images: An Algorithm Based on Minimal Path Selection

2. SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

3. Encoder–decoder network for pixel‐level road crack detection in black‐box images

4. Carr T. A. M. D. Jenkins M. I. Iglesias T. Buggy and G. Morison. 2018. “Road crack detection using a single stage detector based deep neural network.” In Proc. IEEE Workshop on Environmental Energy and Structural Monitoring Systems (EESMS) 1–5. New York: IEEE.

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

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1. Semantic Segmentation of Cracks on Masonry Surfaces Using Deep-Learning Techniques;Practice Periodical on Structural Design and Construction;2024-05

2. A Multitask Fusion Network for Region-Level and Pixel-Level Pavement Distress Detection;Journal of Transportation Engineering, Part B: Pavements;2024-03

3. Hyperparameter Optimization and Importance Ranking in Deep Learning–Based Crack Segmentation;Journal of Computing in Civil Engineering;2024-03

4. Crack Detection via Hierarchical Multiscale Feature Learning and Densely Connected Conditional Random Field;ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering;2024-03

5. 3D vision technologies for a self-developed structural external crack damage recognition robot;Automation in Construction;2024-03

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