Paper Info
Title
Recognition of X-ray Images by Using Revised GMDH-type Neural Networks
Abstract
In this paper, X-ray images of the stomach are recognized by using the revised GMDH (Group Method of Data Handling)-type neural network algorithm. The revised GMDH-type neural networks can automatically organize themselves by using the heuristic self-organization method, which was developed in the GMDH algorithm and is very similar to the Genetic Algorithm. The structural parameters such as the useful input variables, the number of the neurons in the hidden layers, optimum neuron architectures in the hidden layers and the number of feedback loop calculations are automatically selected so as to minimize an error criterion defined as AIC (Akaike's information criterion). AIC can not be used in the conventional multi-layered neural networks using the back propagation method but AIC can be used in the GMDH-type neural network algorithm because the GMDH-type neural networks use the conventional linear regression analysis in order to estimate the connection weights. In this paper, it is shown that this neural network algorithm is very useful in the recognition of X-ray images.
Year
DOI
Venue
2003
10.1007/978-3-540-45226-3_116
LECTURE NOTES IN COMPUTER SCIENCE
Keywords
Field
DocType
akaike information criterion,group method of data handling,back propagation,linear regression,genetic algorithm,neural network,self organization,feedback loop
Heuristic,Akaike information criterion,Pattern recognition,Computer science,Feedback loop,Time delay neural network,Artificial intelligence,Artificial neural network,Backpropagation,Group method of data handling,Genetic algorithm
Conference
Volume
ISSN
Citations 
2774
0302-9743
0
PageRank 
References 
Authors
0.34
1
2
Name
Order
Citations
PageRank
Tadashi Kondo120.74
Abhijit S. Pandya210822.91