Artificial Neural Networks Identification: mayor step towards integrative taxonomy

• Authors: VAŇHARA Jaromír; BOCÁKOVÁ Milada; FEDOR Peter; JANIŠOVÁ Kristýna; PEŇA MÉNDEZ Eladia Maria; MURÁRIKOVÁ Natália; HAVEL Josef
• Year of publication: 2012
• Type: Conference abstract
• MU Faculty or unit: Faculty of Science
• Description: 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.