Abstract. Steganalysis consists in classifying documents as steganographied or genuine. This paper presents a methodology for steganalysis based on a set of 193 features with two m...
Yoan Miche, Patrick Bas, Amaury Lendasse, Christia...
Feature selection for supervised learning can be greatly improved by making use of the fact that features often come in classes. For example, in gene expression data, the genes wh...
Paramveer S. Dhillon, Dean P. Foster, Lyle H. Unga...
It has been shown that features can be selected adaptively for object tracking in changing environments [1]. We propose to use the variance of Mutual Information [2] for online fea...
Though AdaBoost has been widely used for feature selection and classifier learning, many of the selected features, or weak classifiers, are redundant. By incorporating mutual infor...
LinLin Shen, Li Bai, Daniel Bardsley, Yangsheng Wa...
Most image segmentation algorithms optimize some mathematical similarity criterion derived from several low-level image features. One possible way of combining different types of f...