Recognition of damaged letters based on neural network analysis
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17310%2F13%3AA14017Z6" target="_blank" >RIV/61988987:17310/13:A14017Z6 - 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
Recognition of damaged letters based on neural network analysis
Original language description
This paper describes an experimental study based on the application of neural networks for pattern recognition of numbers stamped (imprinted) on ingots. The same task was also solved using fuzzy logic. The ability of all tested neural networks is sufficient to learn all the test patterns, as was demonstrated during experimental works. Unfortunately, amount of training patterns provided by Company KMC Group, s.r.o. were very small and they were very different from test samples. In the article, appropriate types of binarization were discussed so as to extract sufficient information regarding classification via neural networks. There were the optimization of the training set proposed based on the training set analysis. Next, we also proposed way of optimization of parameters belonging to adaptation rules of used neural networks. All experimental results were mutually compared in conclusion.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Mendel 2013
ISBN
978-80-214-4755-4
ISSN
1803-3814
e-ISSN
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Number of pages
6
Pages from-to
209-214
Publisher name
Brno Univerzity of Technology
Place of publication
Brno
Event location
Brno
Event date
Jun 26, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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