NB-CNN: Deep Learning-Based Crack Detection Using Convolutional Neural Network and Naïve Bayes Data Fusion

Regular inspection of nuclear power plant components is important to guarantee safe operations. However, current practice is time consuming, tedious, and subjective, which involves human technicians reviewing the inspection videos and identifying cracks on reactors. A few vision-based crack detectio...

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Bibliographic Details
Published in:	IEEE transactions on industrial electronics (1982) Vol. 65; no. 5; pp. 4392 - 4400
Main Authors:	Chen, Fu-Chen, Jahanshahi, Mohammad R.
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.05.2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Artificial neural networks Bayesian analysis Cameras convolutional neural network (CNN) Crack detection Cracks data fusion Data integration Decision making Deep learning Electric power plants Inspection Military strategy Multisensor fusion Neural networks Nondestructive testing Nuclear electric power generation Nuclear fusion nuclear power plant inspection Nuclear power plants Nuclear reactors Power generation Power plant components Surface cracks Surface morphology Videos
ISSN:	0278-0046, 1557-9948
Online Access:	Get full text
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