@misc{10481/77911,
year = {2009},
url = {https://hdl.handle.net/10481/77911},
abstract = {The steganography problem consists of the identification of
images hiding a secret message, which cannot be seen by visual inspection.
This problem is nowadays becoming more and more important since
the World Wide Web contains a large amount of images, which may be
carrying a secret message. Therefore, the task is to design a classifier,
which is able to separate the genuine images from the non-genuine ones.
However, the main obstacle is that there is a large number of variables
extracted from each image and the high dimensionality makes the feature
selection mandatory in order to design an accurate classifier. This paper
presents a new efficient parallel feature selection algorithm based on the
Forward-Backward Selection algorithm. The results will show how the
parallel implementation allows to obtain better subsets of features that
allow the classifiers to be more accurate.},
organization = {TIN2007-60587, P07-TIC-02768 and P07-TIC-02906,TIC-3928},
organization = {Nokia Foundation,
Finland},
publisher = {Springer},
keywords = {Inteligencia artificial},
keywords = {Artificial intelligence},
title = {Efficient Parallel Feature Selection for Steganography Problems},
author = {Guillén, Alberto and Rojas Ruiz, Ignacio},
}