ORIGINAL PAPER
The neural network type the MLP and RBF as classifying tools in picture analysis
 
 
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Journal of Research and Applications in Agricultural Engineering 2006;51(4):34-39
 
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ABSTRACT
The neuronal identification of pictorial data, with special emphasis on both quantitative & qualitative analysis, is more frequently utilized to gain & deepen the empirical data knowledge. Extraction & then classification of selected picture features, enables one to create computer tools in order to identify these objects presented as, for example, digital pictures. In relationship from this, it seems to be purposeful the search of the modern methods helping educational process in the range of construction as well as exploitation of neuronal models in context of their utilization in picture analysis process. The additional aim of the work was the comparison of neural network of the type MLP and RBF for indication of the optimum classification tool.
REFERENCES (7)
1.
Tadeusiewicz R., Flasiński M. (1991). Rozpoznawanie obrazów: Wydawnictwo Naukowe PWN, Warszawa.
 
2.
Mirkut Zb., Tadeusiewicz R. (2000). Sieci neuronowe tom 6: Akademicka Witryna Wydawnicza EXIT, Warszawa.
 
3.
Boniecki P. (2004). Sieci neuronowe typu MLP oraz RGB jako komplementarne modele aproksymacyjne w procesie predykcji plonu pszenżyta: Journal of Research and Applications in Agricultural Engineering, Poznań, (1'2004), Vol. 49(1), str. 28-33.
 
4.
Kohorda P., Tadeusiewicz R. (1999). Komputerowa analiza i przetwarzanie obrazo w: Drukarnia Narodowa, Kraków.
 
5.
Tadeusiewicz R., (1993). Sieci neuronowe: Akademicka Oficyna Wydawnicza, Warszawa.
 
6.
Boniecki P., Piekarska-Boniecka H. (2004). The SOFM Neural Network in the Process of Identification of Selected Orchard Pests:_Journal of Research and Applications in Agricultural Engineering,Vol 49(4), p. 5-10, Poznań.
 
7.
Bishop C., (1995). Neural Networks for Pattern Recognition: Oxford University Press.
 
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ISSN:1642-686X
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