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Quality Testing for Pressed Raised Character on Metal Label Using GRBF Networks
In accordance with the obvious characteristics of the pressed raised character image and the shortages of the template matching method.a new method of using the general radial-basis function neural network (GRBFN) for testing the quality of the pressed character is presented. The structures and trai...
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Published in: | Key engineering materials 2006-01, Vol.315-316, p.691-695 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Citations: | Items that this one cites |
Online Access: | Get full text |
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Summary: | In accordance with the obvious characteristics of the pressed raised character image and
the shortages of the template matching method.a new method of using the general radial-basis
function neural network (GRBFN) for testing the quality of the pressed character is presented. The
structures and training methods of GRBFN are fully analyzed, as well as the functionality of hidden
layer, excited focus and area. The results show the checker based on GRBFN has highly checking
ratio for the label pressed raised characters. It is suited to the quality testing of raised characters. |
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ISSN: | 1013-9826 1662-9795 1662-9795 |
DOI: | 10.4028/www.scientific.net/KEM.315-316.691 |