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ORIGINAL PAPER
Identification process of corn and barley kernels damages using neural image analysis
Journal of Research and Applications in Agricultural Engineering 2011;56(1):103-105
KEYWORDS
ABSTRACT
The subject of the study was to develop a neural model for identification of mechanical damage to grain caryopses based on digital photographs. The authors has selected a set of universal features that distinguish damaged and healthy caryopses. As a result of this study it has been performed an artificial neural network of a multilayer perceptron type whose identification capacity is near of the human' s one.
REFERENCES (6)
1.
Boniecki P.: Elements of neural modeling in agriculture. Publisher University of Life Sciences in Poznań, 2008. ISBN 978-83-7160-473-7, in Polish.
2.
Boniecki P.: Neural networks of MLP and RBF type as cotnplementary aproximatical models in the triticale crop prediction process. Journal of Research and Applications in Agricultural Engineering, Poznań, 2004, Vol. 49(1), 28-33, in Polish.
3.
Nowakowski K.: Neural identification of selected mechanical damage to kernels. Ph.D. dissertation: Nowakowski K., Poznań, 2008, in Polish.
4.
Nowakowski K.: Neural image analysis. Chapter in a monograph: Elements of agricultural systems engineering. Publisher University of Life Sciences in Poznań, 2008. Wyd. I, ISBN 978-83-7160-501-7, in Polish.
5.
Osowski S.: Neural networks to processing of information. Publishing house of Warsaw Technical University, Warsaw, 2000, in Polish.
6.
Tadeusiewicz R., Lula P.: Statistica Neural Networks PL: Introduction to neural networks. StatSoft Poland, Cracov, 2001, in Polish.
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| eISSN: | 2719-423X |
| ISSN: | 1642-686X |
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