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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 Handbook of Optimization : From Classical to Modern Approach
dc.identifier.isbn 978-3-642-30503-0
dc.date.issued 2013
dc.citation.spage 821
dc.citation.epage 843
dc.event.location Heidelberg
utb.event.state-en Germany
utb.event.state-cs Německo
dc.type bookPart
dc.language.iso en
dc.publisher Springer-Verlag. Berlin
dc.subject steganalysis en
dc.subject artificial neural networks en
dc.subject data mining en
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. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1005906
utb.identifier.rivid RIV/70883521:28140/13:43869836!RIV14-GA0-28140___
utb.identifier.obdid 43870005
utb.source c-riv
dc.date.accessioned 2016-04-28T10:37:22Z
dc.date.available 2016-04-28T10:37:22Z
dc.description.sponsorship P(ED2.1.00/03.0089), P(GA102/09/1680), S, Z(MSM7088352101)
dc.format.extent 1097
utb.identifier.utb-sysno 000077176
utb.identifier.nkp 5554104
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
riv.obor IN
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