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Optimization of artificial neural network structure in the case of steganalysis

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dc.title Optimization of artificial neural network structure in the case of steganalysis en
dc.contributor.author Komínková Oplatková, Zuzana
dc.contributor.author Hološka, Jiří
dc.contributor.author Procházka, Michal
dc.contributor.author Šenkeřík, Roman
dc.contributor.author Jašek, Roman
dc.relation.ispartof Intelligent Systems Reference Library
dc.identifier.issn 1868-4394 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn 978-3-642-30503-0
dc.date.issued 2013
utb.relation.volume 38
dc.citation.spage 821
dc.citation.epage 843
dc.type article
dc.language.iso en
dc.publisher Springer Science+Business Media en
dc.identifier.doi 10.1007/978-3-642-30504-7_32
dc.relation.uri https://link.springer.com/chapter/10.1007/978-3-642-30504-7_32
dc.description.abstract This research introduces a method of steganalysis by means of neural networks and its structure optimization. The main aim is to explain the approach of revealing a hidden content in jpeg files by feed forward neural network with Levenberg-Marquardt training algorithm. This work is also concerned to description of data mining techniques for structure optimization of used neural network. The results showed almost 100% success of detection. © Springer-Verlag Berlin Heidelberg 2013. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1003510
utb.identifier.obdid 43870005
utb.identifier.scopus 2-s2.0-84885457085
utb.source j-scopus
dc.date.accessioned 2013-11-11T08:24:18Z
dc.date.available 2013-11-11T08:24:18Z
utb.contributor.internalauthor Komínková Oplatková, Zuzana
utb.contributor.internalauthor Hološka, Jiří
utb.contributor.internalauthor Procházka, Michal
utb.contributor.internalauthor Šenkeřík, Roman
utb.contributor.internalauthor Jašek, Roman
utb.fulltext.affiliation Zuzana Oplatkova, Jiri Holoska, Michal Prochazka, Roman Senkerik, and Roman Jasek Zuzana Oplatkova · Jiri Holoska · Michal Prochazka · Roman Senkerik · Roman Jasek Tomas Bata University in Zlín, Faculty of Applied Informatics, Nam. T.G. Masaryka 5555, 760 01 Zlín, Czech Republic e-mail: {oplatkova,holoska,mprochazka,senkerik,jasek}@fai.utb.cz
utb.fulltext.dates -
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utb.fulltext.sponsorship This work was supported by the grants: internal grant agency of Tomas Bata University in Zlin IGA/44/FAI/10/D, grant NO. MSM 7088352101 of the Ministry of Education of the Czech Republic, grant of Grant Agency of Czech Republic GACR 102/09/1680 and by the European Regional Development Fund under the Project CEBIATech No. CZ.1.05/2.1.00/03.0089.
utb.fulltext.projects IGA/44/FAI/10/D
utb.fulltext.projects MSM 7088352101
utb.fulltext.projects GACR 102/09/1680
utb.fulltext.projects CZ.1.05/2.1.00/03.0089
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