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New training strategies for RBF neural networks for X-ray agricultural product inspection

✍ Scribed by David Casasent; Xue-wen Chen


Publisher
Elsevier Science
Year
2003
Tongue
English
Weight
260 KB
Volume
36
Category
Article
ISSN
0031-3203

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✦ Synopsis


Classiÿcation of real-time X-ray images of pistachio nuts is discussed. The goal is to reduce the percentage of infested nuts while not rejecting more than a few percent of the good nuts. Radial basis function (RBF) neural network classiÿers are emphasized. New training procedures are developed that allow samples such as those that are near decision boundaries to be treated di erently from other samples. New clustering methods and new cluster classes are advanced to select and separately control various RBF parameters. These advancements are shown to be of use in this application.