Machine Learning Approach to Point Localization System

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17610%2F15%3AA1701E61" target="_blank" >RIV/61988987:17610/15:A1701E61 - isvavai.cz</a>

Výsledek na webu

—

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Machine Learning Approach to Point Localization System

Popis výsledku v původním jazyce

The article introduces point localization systems in 3D Euclidean space based on neural networks. There are two models presented. The first one identified distances between a randomly generated point and a reference points in the defined domain. Then a neural network uses the obtained distances as its inputs to determine the actual position of the point in the domain space. Due to a relatively good accuracy that was obtained during the experimental study, the proposed model based on neural networks was used in the second model as an acoustic Motion Capturing system (MoCap). MoCap system is represented by a neural network that uses obtained distances between transmitters and a receiver as its inputs to determine an actual position of the receiver in space. We also propose a new way to minimize a training set by using ANFIS approach in this specific problem. All obtained results are summarized in the conclusion.

Název v anglickém jazyce

Machine Learning Approach to Point Localization System

Popis výsledku anglicky

The article introduces point localization systems in 3D Euclidean space based on neural networks. There are two models presented. The first one identified distances between a randomly generated point and a reference points in the defined domain. Then a neural network uses the obtained distances as its inputs to determine the actual position of the point in the domain space. Due to a relatively good accuracy that was obtained during the experimental study, the proposed model based on neural networks was used in the second model as an acoustic Motion Capturing system (MoCap). MoCap system is represented by a neural network that uses obtained distances between transmitters and a receiver as its inputs to determine an actual position of the receiver in space. We also propose a new way to minimize a training set by using ANFIS approach in this specific problem. All obtained results are summarized in the conclusion.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

—

Projekt

<a href="/cs/project/ED1.1.00%2F02.0070" target="_blank" >ED1.1.00/02.0070: Centrum excelence IT4Innovations</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název statě ve sborníku

IEEE 13th International Symposium on Applied Machine Intelligence and Informatics

ISBN

978-1-4799-8221-9

ISSN

—

e-ISSN

—

Počet stran výsledku

5

Strana od-do

313-317

Název nakladatele

IEEE

Místo vydání

New York

Místo konání akce

Slovakia, Herľany

Datum konání akce

22. 1. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000380524900051