About: Insect identification using Artificial Neural Networks (ANN)

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	Introduction: The progress in information technology has opened opportunities for the computer-assisted taxonomy. Methods: The use of ANN requires a training database in which specimens, correctly identified by experts, are included. For ANN inputs can be used digital images, optically sensed wing beat frequency spectra, near-infrared reflectance spectra, bioacoustic recordings, chemotaxonomy or morphometry. An ANN model is designed to find a relationship between the characters (=input) and species (=output). The quality of the training set is an essential prerequisite to obtaining reliable identifications. Results: Our case studies used morphometric data mostly. The high percentage of correctly identified specimens (about 97 %) is promising for a wider use of ANN. Conclusions: ANN is cheap and non-destructive suitable also for type material or permanently mounted slides. ANN have the potential to enhance the practice of routine identification with a non-expert as technical help. Introduction: The progress in information technology has opened opportunities for the computer-assisted taxonomy. Methods: The use of ANN requires a training database in which specimens, correctly identified by experts, are included. For ANN inputs can be used digital images, optically sensed wing beat frequency spectra, near-infrared reflectance spectra, bioacoustic recordings, chemotaxonomy or morphometry. An ANN model is designed to find a relationship between the characters (=input) and species (=output). The quality of the training set is an essential prerequisite to obtaining reliable identifications. Results: Our case studies used morphometric data mostly. The high percentage of correctly identified specimens (about 97 %) is promising for a wider use of ANN. Conclusions: ANN is cheap and non-destructive suitable also for type material or permanently mounted slides. ANN have the potential to enhance the practice of routine identification with a non-expert as technical help. (en)
Title	Insect identification using Artificial Neural Networks (ANN) Insect identification using Artificial Neural Networks (ANN) (en)
skos:prefLabel	Insect identification using Artificial Neural Networks (ANN) Insect identification using Artificial Neural Networks (ANN) (en)
skos:notation	RIV/00216224:14310/08:00042029!RIV11-MSM-14310___
http://linked.open...avai/riv/aktivita	S Z
http://linked.open...avai/riv/aktivity	S, Z(MSM0021622416)
http://linked.open...vai/riv/dodaniDat	2011
http://linked.open...aciTvurceVysledku	Fedor, Peter Havel, Josef Malenovský, Igor Muráriková, Natália Vaňhara, Jaromír
http://linked.open.../riv/druhVysledku	O - Ostatní výsledky nezařaditelné do žádného z výše uvedených druhů výsledku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Masarykova univerzita / Přírodovědecká fakulta
http://linked.open...dnocenehoVysledku	372578
http://linked.open...ai/riv/idVysledku	RIV/00216224:14310/08:00042029
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Artificial Neural Networks; ANN; Artificial Intelligence; Entomology; Identification (en)
http://linked.open.../riv/klicoveSlovo	Entomology ANN Artificial Neural Networks Identification Artificial Intelligence
http://linked.open...ontrolniKodProRIV	[BE556C8674B4]
http://linked.open...in/vavai/riv/obor	EG
http://linked.open...ichTvurcuVysledku	5 (xsd:int)
http://linked.open...cetTvurcuVysledku	5 (xsd:int)
http://linked.open...UplatneniVysledku	2008
http://linked.open...iv/tvurceVysledku	Fedor, Peter Havel, Josef Malenovský, Igor Muráriková, Natália Vaňhara, Jaromír
http://linked.open...n/vavai/riv/zamer	Diversity of Biotic Communities and Populations: Causal Analysis of variation in space and time
http://localhost/t...ganizacniJednotka	14310

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