A major issue in computer aided celiac disease diagnosis is the prevalence of substantial intra-class and even intra-image variations. A method which splits the images into a set of smaller ones and finally applies a decision level fusion turned out to be a powerful technique to address these problems and to boost the classification accuracy. This is especially true if using Local Binary Patter...

Photometric redshifts have been regarded as efficient and effective measures for studying the statistical properties of galaxies and their evolution. In this paper, we introduce SVM_Light, a freely available software package using support vector machines (SVM) for photometric redshift estimation. This technique shows its superiorities in accuracy and efficiency. It can be applied to huge volume...

We present the results of comparisons of performances of several tracking or/and analysis codes. The basic purpose of this program was to assess reliability and accuracy of these codes, Le. to determine the so-called "error bars" for the predicted values of tunes and other lattice functions as a minimum and, if possible, to discover potential difficulties with underlying physical models in thes...

Constant growing of the mean age of the population and bottleneck created at the entry of institutions makes telemedicine for elderly people an actual challenge largely explored. It requires recognizing the behavior and actions of a person inside his home with non-intrusive sensors and to process data to check his evolution. This paper presents the results of the study of prior introduction, in...

Recent studies disclose that maximizing the minimum margin like support vector machines does not necessarily lead to better generalization performances, and instead, it is crucial to optimize the margin distribution. Although it has been shown that for binary classification, characterizing the margin distribution by the firstand second-order statistics can achieve superior performance. It still...

In this paper, we introduce a new approach to identify people in multi-camera based on AdaBoost descriptors cascade. Given the complexity of this task, we propose a new regional color feature vector based on intra and inter color histograms fusion to characterize a person in multi-camera. This descriptor is, then, integrated into an extensive comparative study with several existing color, textu...

Identifying discriminative motifs underlying the functionality and evolution of organisms is a major challenge in computational biology. Machine learning approaches such as support vector machines (SVMs) achieve state-of-the-art performances in genomic discrimination tasks, but--due to its black-box character--motifs underlying its decision function are largely unknown. As a remedy, positional ...

The global financial crisis at the end of 2007 financially influenced various countries, including Indonesia. Because Indonesia achieved highest growth in the Southeast Asia region during the recession, global investors shift their investment in Indonesia market. Therefore, it is very important to explore the stock dynamism in Indonesia. We propose a hybrid approach of fuzzy theorem, support ve...

This paper studies the reliance of a Gaussian Mixture Model (GMM) based closed-set Speaker Identification system on model convergence and describes methods to improve this convergence. It shows that the reason why the Vector Quantisation GMMs (VQGMMs) outperform a simple GMM is mainly due to decreasing the complexity of the data during training. In addition, it is shown that the VQGMM system is...

High-Throughput technologies provide genomic and trascriptomic data that are suitable for biomarker detection for classification purposes. However, the high dimension of the output of such technologies and the characteristics of the data sets analysed represent an issue for the classification task. Here we present a new feature selection method based on three steps to detect class-specific biom...