This paper presents a new framework for generating triangular meshes from textured color images. The proposed framework combines a texture classification technique, called W-operator, with Imesh, a method originally conceived to generate simplicial meshes from gray scale images. An extension of W-operators to handle textured color images is proposed, which employs a combination of RGB and HSV c...

In this article, we describe and interpret a set of acoustic and linguistic features that characterise emotional/emotion-related user states – confined to the one database processed: four classes in a German corpus of children interacting with a pet robot. To this end, we collected a very large feature vector consisting of more than 4000 features extracted at different sites. We performed exten...

An important problem in bioinformatics is the inference of gene regulatory networks (GRN) from temporal expression profiles. In general, the main limitations faced by GRN inference methods is the small number of samples with huge dimensionalities and the noisy nature of the expression measurements. In face of these limitations, alternatives are needed to get better accuracy on the GRNs inferenc...

Sequential search methods characterized by a dynamically changing number of features included or eliminated at each step, henceforth "floating" methods, are presented. They are shown to give very good results and to be computationally more effective than the branch and bound method.

Writer identification has become a hot research topic in the fields of pattern recognition, forensic document analysis, criminal justice system, etc. The goal this is to propose an efficient approach for writer based on online handwritten Kanji characters. We collected 47,520 samples from 33 people who wrote 72 handwritten-based characters 20 times. extracted features handwriting data and propo...

In this paper, two strategies to compute the support sets system for the supervised classifier ALVOT (voting algorithms) using sequential floating selection are presented. ALVOT is a supervised classification model based on the partial precedence principle, therefore, it needs, as feature selection, a set of features subsets, this set is called support sets system. The sequential floating selec...

Feature selection process is used to reduce the feature vector length and identify thediscriminative features. Many acoustic-phonetic features including Mel-Frequency CepstralCoefficient (MFCC), Energy, Pitch, Zero-crossing, spectrum were tested individually for Arabicmispronunciation detection using three classifiers; Random Forest, Bayesian classifier, BaggedSupport Vector Machine (SVM). The ...

Abs t rac t . In this paper we examine the edge searching problem on pseudo 3-sided solid orthoconvex grids. We obtain a closed formula that expresses the minimum number of searchers required to search a pseudo 3-sided solid orthoconvex grid. From that formula and a rather straight forward algorithm we show that the problem is in P. We obtain a parallel version of that algorithm that places the...

Transfer learning is a promising approach for reducing training time in brain-computer interface (BCI). However, how to effectively transfer data from previous users new user poses huge challenge. This paper presents novel that combines alignment and source subject selection motor imagery (MI) based BCIs. The former achieved by reference matrix the regularization of two matrices estimated Riema...

We present a model of parallel search in theorem proving for forward-reasoning strategies, with contraction and distributed search. We extend to parallel search the bounded-search-spaces approach to the measurement of infinite search spaces, capturing both the advantages of parallelization, e.g., the subdivision of work, and its disadvantages, e.g., the cost of communication, in terms of search...