Zernike‐moment measurement of thin‐crack width in images enabled by dual‐scale deep learning-Reference-Cited by-同舟云学术

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Zernike‐moment measurement of thin‐crack width in images enabled by dual‐scale deep learning

Published:2018-12-11 Issue:5 Volume:34 Page:367-384
ISSN:1093-9687
Container-title:Computer-Aided Civil and Infrastructure Engineering
language:en
Short-container-title:Computer‐Aided Civil and Infrastructure Engineering

Author:

Ni FuTao¹,Zhang Jian¹²,Chen ZhiQiang³

Affiliation:

1. School of Civil EngineeringSoutheast University Nanjing China

2. Jiangsu Key Laboratory of Engineering MechanicsSoutheast University Nanjing China

3. Department of Civil and Mechanical EngineeringUniversity of Missouri‐Kansas City Kansas City Missouri

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Graphics and Computer-Aided Design,Computer Science Applications,Civil and Structural Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/mice.12421

Reference57 articles.

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

2. Flaw detection in radiographic weldment images using morphological watershed segmentation technique

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

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

5. A texture-Based Video Processing Methodology Using Bayesian Data Fusion for Autonomous Crack Detection on Metallic Surfaces

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