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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 Komínková Oplatková, Zuzana Hološka, Jiří Procházka, Michal Šenkeřík, Roman Jašek, Roman
dc.relation.ispartof Handbook of Optimization : From Classical to Modern Approach
dc.identifier.isbn 978-3-642-30503-0 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
utb.identifier.rivid RIV/70883521:28140/13:43869836!RIV14-GA0-28140___
utb.identifier.obdid 43870005
utb.source c-riv 2016-04-28T10:37:22Z 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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