Neural Identification of Chosen Apple Pests Using Algorithm LVQ

The aim of this work was a neural identification of selected apple tree orchard pests in Poland. The classification was conducted on the basis of graphical information coded in the form of selected geometric characteristics of agrofags, presented on digital images. A neural classification model is presented in this paper, optimized using learning files acquired on the basis of information contained in digital photographs of pests. There has been identified 6 selected apple pests, the most commonly encountered in Polish orchards, has been addressed. In order to classify the chosen agrofags, neural networks type SOFM (Self-Organizing Feature Map) methods supported LVQ (Learning Vector Quantization) algorithms were utilized, supported by digital analysis of image techniques.

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