SIFT Feature Extraction Applied in SVM Classification
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27120%2F22%3A10250375" target="_blank" >RIV/61989100:27120/22:10250375 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27240/22:10250375
Result on the web
<a href="https://aip.scitation.org/doi/abs/10.1063/5.0081373" target="_blank" >https://aip.scitation.org/doi/abs/10.1063/5.0081373</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1063/5.0081373" target="_blank" >10.1063/5.0081373</a>
Alternative languages
Result language
angličtina
Original language name
SIFT Feature Extraction Applied in SVM Classification
Original language description
In this paper, we explore the image feature extraction approach called Scale-Invariant Feature Transform. We use the extracted features for training and testing of a classification technique, the Support Vector Machines. For the benchmarks, we train and test the classifier using features extracted from real image data. This model, we compare with a classification model trained using pixel values.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10102 - Applied mathematics
Result continuities
Project
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Continuities
V - Vyzkumna aktivita podporovana z jinych verejnych zdroju
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
AIP Conference Proceedings. Volume 2425
ISBN
978-0-7354-4182-8
ISSN
0094-243X
e-ISSN
1551-7616
Number of pages
4
Pages from-to
"neuvedeno"
Publisher name
AIP Publishing
Place of publication
Melville
Event location
Rhodos
Event date
Sep 17, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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