Use of neural networks library for material defect detection diagnosis
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F11%3A86080851" target="_blank" >RIV/61989100:27240/11:86080851 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-642-21762-3_58" target="_blank" >http://dx.doi.org/10.1007/978-3-642-21762-3_58</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-642-21762-3_58" target="_blank" >10.1007/978-3-642-21762-3_58</a>
Alternative languages
Result language
angličtina
Original language name
Use of neural networks library for material defect detection diagnosis
Original language description
Aim of this project is to prepare support for design and realization of application, which is developed in object orientated programming language C#. This application classifies data that are obtained within industrial processes. Data used in this project was received during measurement of material diagnostics and its structural defects. Core of developed application is based on neural networks design, which is capable to classify whether the material has defect or not. Before classification itself it is necessary to set structural parameters of the neural network to obtain a good quality results. Afterwards application outputs are compared with outputs from Statistica programme, which is also used for classification purposes.
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/1M0567" target="_blank" >1M0567: Centre for Applied Cybernetics</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Lecture Notes in Electrical Engineering
ISSN
1876-1100
e-ISSN
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Volume of the periodical
100 LNEE
Issue of the periodical within the volume
4
Country of publishing house
DE - GERMANY
Number of pages
8
Pages from-to
447-454
UT code for WoS article
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EID of the result in the Scopus database
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