The F-transform Plus PCA Dimensionality Reduction with Application to Pattern Recognition in Large Databases
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17610%2F18%3AA1901X6O" target="_blank" >RIV/61988987:17610/18:A1901X6O - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
The F-transform Plus PCA Dimensionality Reduction with Application to Pattern Recognition in Large Databases
Original language description
Two distinguished properties of the F-transform:the best approximation in a local sense and the reductionin dimension imply the fact that the F-transform has manysuccessful applications. In the first part, we propose another wayof computing the F-transform components of a functional data.This way is based on the particular dimensionality reductionalgorithm named Laplacian eigenmaps. In the second part,we strengthen the effect of F-transform-based dimensionalityreduction by applying the PCA reduction method over theF0- or F1- transform results. We demonstrate the efficiency ofthe proposed combinations F0zT+PCA and F1zT+PCA on theproblem of patter recognition in a large database. We compareboth combinations with other relevant techniques (besides other,LENET-like CNN) and show that they outperform them fromthe computation time and success rate points of view.
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
10101 - Pure mathematics
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2018 IEEE Symposium Series on Computational Intelligence (SSCI 2018)
ISBN
978-1-5386-9275-2
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
1020-1026
Publisher name
IEEE publishing services
Place of publication
Bengaluru
Event location
Bengaluru
Event date
Nov 18, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000459238800138