Neural Network as a Tool for Detection of Wine Grapes
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25530%2F16%3A39901932" target="_blank" >RIV/00216275:25530/16:39901932 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-33625-1_21" target="_blank" >http://dx.doi.org/10.1007/978-3-319-33625-1_21</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-33625-1_21" target="_blank" >10.1007/978-3-319-33625-1_21</a>
Alternative languages
Result language
angličtina
Original language name
Neural Network as a Tool for Detection of Wine Grapes
Original language description
The recognition of wine grapes in real-life images is a serious issue solved by researches dealing with precision viticulture. The detection of wine grapes of red varieties is a well mastered problem. On the other hand, the detection of white varieties is still a challenging task. In this contribution, detectors designed for recognition of white wine grapes in real-life images are introduced and evaluated. Two representations of object images are considered in this paper; namely, vector of normalized pixel intensities and histograms of oriented gradients. In both cases, classifiers are realized using feedforward multilayer neural networks. The detector based on the histograms of oriented gradients has proven to be very effective by cross-validation. The results obtained by its evaluation on independent testing data are slightly worse; however, still very good. On the other hand, the representation using the vector of normalized pixel intensities was stated as insufficient.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
BD - Information theory
OECD FORD branch
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Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Artificial Intelligence Perspectives in Intelligent Systems : Proceedings of the 5th Computer Science On-line Conference 2016 (CSOC2016). Vol 1
ISBN
978-3-319-33625-1
ISSN
2194-5357
e-ISSN
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Number of pages
11
Pages from-to
225-235
Publisher name
Springer International Publishing AG
Place of publication
Cham
Event location
Prague
Event date
Apr 27, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000385237600021