Is Ensemble Classifier Needed for Steganalysis in High-Dimensional Feature Spaces?
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F15%3A00237781" target="_blank" >RIV/68407700:21230/15:00237781 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/WIFS.2015.7368597" target="_blank" >http://dx.doi.org/10.1109/WIFS.2015.7368597</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/WIFS.2015.7368597" target="_blank" >10.1109/WIFS.2015.7368597</a>
Alternative languages
Result language
angličtina
Original language name
Is Ensemble Classifier Needed for Steganalysis in High-Dimensional Feature Spaces?
Original language description
The ensemble classifier, based on Fisher Linear Discriminant base learners, was introduced specifically for steganalysis of digital media, which currently uses high-dimensional feature spaces. Presently it is probably the most used method to design supervised classifier for steganalysis of digital images because of its good detection accuracy and small computational cost. It has been assumed by the community that the classifier implements a non-linear boundary through pooling binary decision of individual classifiers within the ensemble. This paper challenges this assumption by showing that linear classifier obtained by various regularizations of the FLD can perform equally well as the ensemble. Moreover it demonstrates that using state of the art solvers linear classifiers can be trained more efficiently and offer certain potential advantages over the original ensemble leading to much lower computational complexity than the ensemble classifier. All claims are supported experimentally
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 7th International Workshop on Forensics and Security
ISBN
978-1-4673-6802-5
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
1-6
Publisher name
IEEE Signal Processing Society
Place of publication
New Jersey
Event location
Rome
Event date
Nov 16, 2015
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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