-------------------------------------------------------------------ABSTRACT----------------------------------------------------------------Nowadays various applications are available that claim to extract the correct information from such colored image databases which have different kinds of images and their own semantics. During information extraction based on the content of images various kin...

in the current iris recognition systems, noise removing step is only used to detect noisy parts of the iris region and features extracted from there will be excluded in matching step. whereas depending on the filter structure used in feature extraction, the noisy parts may influence relevant features. to the best of our knowledge, the effect of noise factors on feature extraction has not been c...

biomedical datasets usually include a large number of features relative to the number of samples. however, some data dimensions may be less relevant or even irrelevant to the output class. selection of an optimal subset of features is critical, not only to reduce the processing cost but also to improve the classification results. to this end, this paper presents a hybrid method of filter and wr...

in this study, a method for determining the location and extent of myocardial infarction using body surface potential map data that is obtained from physionet challenge 2007 database has been suggested. this data is related to four patients with myocardial infarction that we used from two patients as training set to determine rules, and from two other patients for testing set and the conclusion...

When the number of training samples is limited, feature reduction plays an important role in classification of hyperspectral images. In this paper, we propose a supervised feature extraction method based on discriminant analysis (DA) which uses the first principal component (PC1) to weight the scatter matrices. The proposed method, called DA-PC1, copes with the small sample size problem and has...

A multi voxel pattern analysis classi cation framework suitable for neuroimaging data is introduced. The framework includes a novel feature extraction method that uses local modeling based on domain speci c knowledge, and therefore, can produce better whole-brain global classi cation performance using a smaller number of features. In particular, the method includes spherical searchlights in com...