Sparse Versions of Optimized Centroids
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F22%3A00562370" target="_blank" >RIV/67985807:_____/22:00562370 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/IJCNN55064.2022.9892838" target="_blank" >http://dx.doi.org/10.1109/IJCNN55064.2022.9892838</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/IJCNN55064.2022.9892838" target="_blank" >10.1109/IJCNN55064.2022.9892838</a>
Alternative languages
Result language
angličtina
Original language name
Sparse Versions of Optimized Centroids
Original language description
Centroid-based methods have an established place in a variety of tasks including object localization in images. A sophisticated method for constructing optimal centroids and corresponding weights has been proposed only recently. In order to reduce the computational demands of applying the optimal centroid, several novel sparse versions of the optimal centroids are proposed here, which are based on trimming away some of their pixels. Suitable novel sparse versions bring improvements compared to available optimal centroids. At the same time, some of the sparse optimal centroids (especially the method with thresholded optimal weights) turn out to be robust to noise in the images.
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
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA22-02067S" target="_blank" >GA22-02067S: AppNeCo: Approximate Neurocomputing</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
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
2022 International Joint Conference on Neural Networks (IJCNN) Proceedings
ISBN
978-1-7281-8671-9
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
1-7
Publisher name
IEEE
Place of publication
Piscataway
Event location
Padua
Event date
Jul 18, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000867070907075