Robustness Aspects 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_____%2F23%3A00580817" target="_blank" >RIV/67985807:_____/23:00580817 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/978-3-031-09034-9_22" target="_blank" >https://doi.org/10.1007/978-3-031-09034-9_22</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-09034-9_22" target="_blank" >10.1007/978-3-031-09034-9_22</a>
Alternative languages
Result language
angličtina
Original language name
Robustness Aspects of Optimized Centroids
Original language description
Centroids are often used for object localization tasks, supervised segmentation in medical image analysis, or classification in other specific tasks. This paper starts by contributing to the theory of centroids by evaluating the effect of modified illumination on the weighted correlation coefficient. Further, robustness of various centroid-based tools is investigated in experiments related to mouth localization in non-standardized facial images or classification of high-dimensional data in a matched pairs design. The most robust results are obtained if the sparse centroid-based method for supervised learning is accompanied with an intrinsic variable selection. Robustness, sparsity, and energy-efficient computation turn out not to contradict the requirement on the optimal performance of the centroids.
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
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Classification and Data Science in the Digital Age
ISBN
978-3-031-09033-2
ISSN
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e-ISSN
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Number of pages
9
Pages from-to
193-201
Publisher name
Springer
Place of publication
Cham
Event location
Porto
Event date
Jul 19, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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