Deep Learning-Based Crack Damage Detection Using Convolutional Neural Networks-Reference-Cited by-同舟云学术

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Deep Learning-Based Crack Damage Detection Using Convolutional Neural Networks

Published:2017-03-23 Issue:5 Volume:32 Page:361-378
ISSN:1093-9687
Container-title:Computer-Aided Civil and Infrastructure Engineering
language:en
Short-container-title:Computer-Aided Civil and Infrastructure Engineering

Author:

Cha Young-Jin¹,Choi Wooram¹,Büyüköztürk Oral²

Affiliation:

1. Department of Civil Engineering; University of Manitoba; Winnipeg MB Canada

2. Department of Civil and Environmental Engineering; Massachusetts Institute of Technology; Cambridge MA USA

Publisher

Wiley

Subject

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

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1111/mice.12263/fullpdf

Reference52 articles.

1. Analysis of edge-detection techniques for crack identification in bridges;Abdel-Qader;Journal of Computing in Civil Engineering,2003

2. Enhanced probabilistic neural network with local decision circles: a robust classifier;Ahmadlou;Integrated Computer-Aided Engineering,2010

3. Flaw detection in radiographic weldment images using morphological watershed segmentation technique;Alaknanda;NDT & E International,2009

4. Practical Recommendations for Gradient-Based Training of Deep Architectures

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