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@proceedings{1092086,
author = {Vaňhara, Jaromír and Bocáková, Milada and Fedor, Peter and Janišová, Kristýna and Peňa Méndez, Eladia Maria and Muráriková, Natália and Havel, Josef},
booktitle = {Integrative biology: From ecology to molecules},
keywords = {ANN;insects;integrative taxonomy},
language = {eng},
title = {Artificial Neural Networks Identification: mayor step towards integrative taxonomy},
url = {http://bcz.ulb.ac.be/19thBCZ/Program_files/Program%2019th%20BCZ.pdf},
year = {2012}
}
TY - CONF
ID - 1092086
AU - Vaňhara, Jaromír - Bocáková, Milada - Fedor, Peter - Janišová, Kristýna - Peňa Méndez, Eladia Maria - Muráriková, Natália - Havel, Josef
PY - 2012
TI - Artificial Neural Networks Identification: mayor step towards integrative taxonomy
KW - ANN;insects;integrative taxonomy
UR - http://bcz.ulb.ac.be/19thBCZ/Program_files/Program%2019th%20BCZ.pdf
L2 - http://bcz.ulb.ac.be/19thBCZ/Program_files/Program%2019th%20BCZ.pdf
N2 - Identification in entomology, based on several independent methodological accesses, is not frequent. Artificial Neural Networks (ANN) are used here, as a part of an integrative taxonomy approach, together with morphological or molecular evaluation. The advantages of ANN include an ability to learn from examples and to generalize observed characters. ANN are able to help us not only with species identification but also with resolution of some taxonomic problems.
ER -
VAŇHARA, Jaromír, Milada BOCÁKOVÁ, Peter FEDOR, Kristýna JANIŠOVÁ, Eladia Maria PEŇA MÉNDEZ, Natália MURÁRIKOVÁ a Josef HAVEL. Artificial Neural Networks Identification: mayor step towards integrative taxonomy. In \textit{Integrative biology: From ecology to molecules}. 2012.
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