Detection of Grapes in Natural Environment Using Feedforward Neural Network as a Classifier

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25530%2F16%3A39902004" target="_blank" >RIV/00216275:25530/16:39902004 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Detection of Grapes in Natural Environment Using Feedforward Neural Network as a Classifier

Popis výsledku v původním jazyce

The recognition of wine grapes in images acquired in natural environment is a serious issue solved by researches dealing with precision viticulture. The detection of wine grapes of red kinds is a well managed problem. On the other hand, the detection of white grapes is still a challenging task. In this contribution, the classifier for white wine grapes recognition is introduced and evaluated. The classifier is based on an artificial neural network and is used in two ways which differ in image representation. Namely, the pixel intensities and histogram of oriented gradients are used for the representation of images. Then, feedforward multilayer neural network is applied as a classifier. The classifiers based on the histograms of oriented gradients seemed to be very effective - they were almost error free from the cross validation point of view and they performed well with the independent testing data sets, too. On the other hand, the representation using pixel intensities was stated as insufficient for classification using our approach.

Název v anglickém jazyce

Detection of Grapes in Natural Environment Using Feedforward Neural Network as a Classifier

Popis výsledku anglicky

The recognition of wine grapes in images acquired in natural environment is a serious issue solved by researches dealing with precision viticulture. The detection of wine grapes of red kinds is a well managed problem. On the other hand, the detection of white grapes is still a challenging task. In this contribution, the classifier for white wine grapes recognition is introduced and evaluated. The classifier is based on an artificial neural network and is used in two ways which differ in image representation. Namely, the pixel intensities and histogram of oriented gradients are used for the representation of images. Then, feedforward multilayer neural network is applied as a classifier. The classifiers based on the histograms of oriented gradients seemed to be very effective - they were almost error free from the cross validation point of view and they performed well with the independent testing data sets, too. On the other hand, the representation using pixel intensities was stated as insufficient for classification using our approach.

Druh

D - Stať ve sborníku

CEP obor

BD - Teorie informace

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2016

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of 2016 SAI Computing Conference

ISBN

978-1-4673-8460-5

ISSN

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e-ISSN

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Počet stran výsledku

5

Strana od-do

1330-1334

Název nakladatele

IEEE (Institute of Electrical and Electronics Engineers)

Místo vydání

New York

Místo konání akce

Londýn

Datum konání akce

13. 7. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000389451900194