Bio-inspired Model of Spatial Cognition

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F11%3A00190983" target="_blank" >RIV/68407700:21230/11:00190983 - isvavai.cz</a>

Výsledek na webu

<a href="http://bio.felk.cvut.cz/~vavrecka/articles/vavrecka_ICONIP2011.pdf" target="_blank" >http://bio.felk.cvut.cz/~vavrecka/articles/vavrecka_ICONIP2011.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Bio-inspired Model of Spatial Cognition

Popis výsledku v původním jazyce

We present the results of an ongoing research in the area of symbol grounding. We develop a biologically inspired model for grounding the spatial terms that employs separate visual what and where subsystems that are integrated with the symbolic linguistic subsystem in the simplified neural model. The model grounds color, shape and spatial relations of two objects in 2D space. The images with two objects are presented to an artificial retina and five-word sentences describing them (e.g. ``Red box above green circle'') with phonological encoding serve as auditory inputs. The integrating multimodal module is implemented by Self-Organizing Map or Neural Gas algorithms in the second layer. We found out that using NG leads to better performance especially incase of the scenes with higher complexity, and current simulations also reveal that splitting the visual information and simplifying the objects to rectangular monochromatic boxes facilitates the performance of the where system and henc

Název v anglickém jazyce

Bio-inspired Model of Spatial Cognition

Popis výsledku anglicky

We present the results of an ongoing research in the area of symbol grounding. We develop a biologically inspired model for grounding the spatial terms that employs separate visual what and where subsystems that are integrated with the symbolic linguistic subsystem in the simplified neural model. The model grounds color, shape and spatial relations of two objects in 2D space. The images with two objects are presented to an artificial retina and five-word sentences describing them (e.g. ``Red box above green circle'') with phonological encoding serve as auditory inputs. The integrating multimodal module is implemented by Self-Organizing Map or Neural Gas algorithms in the second layer. We found out that using NG leads to better performance especially incase of the scenes with higher complexity, and current simulations also reveal that splitting the visual information and simplifying the objects to rectangular monochromatic boxes facilitates the performance of the where system and henc

Druh

D - Stať ve sborníku

CEP obor

AN - Psychologie

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2011

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Neural Information Processing

ISBN

978-3-642-24954-9

ISSN

0302-9743

e-ISSN

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Počet stran výsledku

8

Strana od-do

443-450

Název nakladatele

Springer

Místo vydání

Heidelberg

Místo konání akce

Shanghai

Datum konání akce

14. 11. 2011

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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