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A Novel Algorithm for Detecting Air Holes in Steel Pipe Welding Based on Hopfield Neural Network
Haier International Training Center, Qingdao, China July 30-August 01
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/SNPD.2007.425Eighth ACIS International Conference ...
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Gao Weixin, Tang Nan, Mu Xiangyang, "A Novel Algorithm for Detecting Air Holes in Steel Pipe Welding Based on Hopfield Neural Network," Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, ACIS International Conference on, vol. 1, pp. 79-83, Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007), 2007.
 
 
BibTex
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@article{ 10.1109/SNPD.2007.425,
author = {Gao Weixin and Tang Nan and Mu Xiangyang},
title = {A Novel Algorithm for Detecting Air Holes in Steel Pipe Welding Based on Hopfield Neural Network},
journal ={Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, ACIS International Conference on},
volume = {1},
year = {2007},
isbn = {0-7695-2909-7},
pages = {79-83},
doi = {http://doi.ieeecomputersociety.org/10.1109/SNPD.2007.425},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, ACIS International Conference on
TI - A Novel Algorithm for Detecting Air Holes in Steel Pipe Welding Based on Hopfield Neural Network
SN - 0-7695-2909-7
SP79
EP83
A1 - Gao Weixin,
A1 - Tang Nan,
A1 - Mu Xiangyang,
PY - 2007
KW - null
VL - 1
JA - Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, ACIS International Conference on
ER -
 
Gao Weixin, Xian Shiyou University, China
Tang Nan, Xian Shiyou University, China
Mu Xiangyang, Xian Shiyou University, China
The paper segment x-ray images of steel pipe welding to assess the quality of welding. Image segmentation is posed as an optimization problem, and is correlated with the energy function of the multistage Hopfield neural network. The algorithm for optimization and the principle of selecting coefficient are also given. The algorithm is easy to be programmed. As an application, we successfully segment some real industrial welding x-ray images.
Citation:
Gao Weixin, Tang Nan, Mu Xiangyang, "A Novel Algorithm for Detecting Air Holes in Steel Pipe Welding Based on Hopfield Neural Network," snpd, vol. 1, pp.79-83, Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007), 2007
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