Convolutional generalization of fuzzy logic analysis

Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17310%2F18%3AA2101VYB" target="_blank" >RIV/61988987:17310/18:A2101VYB - isvavai.cz</a>
Výsledek na webu
<a href="http://dx.doi.org/10.1063/1.5079070" target="_blank" >http://dx.doi.org/10.1063/1.5079070</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1063/1.5079070" target="_blank" >10.1063/1.5079070</a>

Jazyk výsledku
angličtina
Název v původním jazyce
Convolutional generalization of fuzzy logic analysis
Popis výsledku v původním jazyce
This article focuses on the theoretical background for the use of a convolution kernels for the purposes of patternrecognition by Fuzzy Logic Analysis (FLA). The fuzzy convolutional approach is a generalization of standard FLA. The standardFLA is based on comparing part of the image with adequate parts of its pattern where each part of the image is representedby a individual pixel. The Fuzzy convolutional approach extends original FLA using convolutional kernels that allow to includeinformation from neighbouring parts of the recognized image.
Název v anglickém jazyce
Convolutional generalization of fuzzy logic analysis
Popis výsledku anglicky
This article focuses on the theoretical background for the use of a convolution kernels for the purposes of patternrecognition by Fuzzy Logic Analysis (FLA). The fuzzy convolutional approach is a generalization of standard FLA. The standardFLA is based on comparing part of the image with adequate parts of its pattern where each part of the image is representedby a individual pixel. The Fuzzy convolutional approach extends original FLA using convolutional kernels that allow to includeinformation from neighbouring parts of the recognized image.

Rok uplatnění
2018
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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