Artificial neural networks for fly identification: A case study from the genera <Emphasis Type="Italic">Tachina</Emphasis> and <Emphasis Type="Italic">Ectophasia</Emphasis> (Diptera,Tachinidae) |
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Authors: | Jaromír Vaňhara Natália Muráriková Igor Malenovský Josef Havel |
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Institution: | (1) Faculty of Science, Institute of Botany and Zoology, Masaryk University, Kotlářská 2, CZ-61137 Brno, Czech Republic;(2) Department of Entomology, Moravian Museum, Hviezdoslavova 29a, CZ-62700 Brno, Czech Republic;(3) Faculty of Science, Department of Analytical Chemistry, Masaryk University, Kotlářská 2, CZ-61137 Brno, Czech Republic |
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Abstract: | The classification methodology based on morphometric data and supervised artificial neural networks (ANN) was tested on five
fly species of the parasitoid genera Tachina and Ectophasia (Diptera, Tachinidae). Objects were initially photographed, then digitalized; consequently the picture was scaled and measured
by means of an image analyser. The 16 variables used for classification included length of different wing veins or their parts
and width of antennal segments. The sex was found to have some influence on the data and was included in the study as another
input variable. Better and reliable classification was obtained when data from both the right and left wings were entered,
the data from one wing were however found to be sufficient. The prediction success (correct identification of unknown test
samples) varied from 88 to 100% throughout the study depending especially on the number of specimens in the training set.
Classification of the studied Diptera species using ANN is possible assuming a sufficiently high number (tens) of specimens
of each species is available for the ANN training. The methodology proposed is quite general and can be applied for all biological
objects where it is possible to define adequate diagnostic characters and create the appropriate database. |
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Keywords: | artificial neural networks species identification Diptera Tachinidae Tachina Ectophasia parasitoids |
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