This paper addresses the multi-view action recognition problem with a local segment similarity voting scheme, upon which we build a novel multi-sensor fusion method. The recently proposed random forests classifier is used to map the local segment features to their corresponding prediction histograms. We compare the results of our approach with those of the baseline Bag-of-Words (BoW) and the Na...

This paper presents a framework for multiclass vehicle type (Make and Model) identification based on oriented contour points. A method to construct a model from several frontal vehicle images is presented. Employing this model, three voting algorithms and a distance error allows to measure the similarity between an input instance and the data bases classes. These scores could be combined to des...

A new classiier using neighborhood information in the framework of the Dempster-Shafer theory of evidence has recently been introduced. This approach consists in considering each neighbor of a pattern to be classiied as an item of evidence supporting certain hypotheses concerning the class membership of that pattern. In this paper, an adap-tive version of this method is proposed, in which the p...

A computer aided diagnosis system aiming to classify liver tissue from computed tomography images is presented. For each region of interest five distinct sets of texture features were extracted. Two different ensembles of classifiers were constructed and compared. The first one consists of five Neural Networks (NNs), each using as input either one of the computed texture feature sets or its red...

Sentiment analysis is the process of identifying the subjective information in the source materials towards an entity. It is a subfield of text and web mining. Web is a rich and progressively expanding source of information. Sentiment analysis can be modelled as a text classification problem. Text classification suffers from the high dimensional feature space and feature sparsity problems. The ...

SUMMARY GeneCluster 2.0 is a software package for analyzing gene expression and other bioarray data, giving users a variety of methods to build and evaluate class predictors, visualize marker lists, cluster data and validate results. GeneCluster 2.0 greatly expands the data analysis capabilities of GeneCluster 1.0 by adding classification, class discovery and permutation test methods. It includ...

Knowledge Discovery in Dataset (KDD) plays a vital role in information analysis and retrieval based applications. Quality of data is the most indispensable component of KDD. The factor which affects the quality of datasets is presence of missing values. The data collected from the real world often contains serious data quality troubles such as incomplete, redundant, inconsistent, and/or noisy d...

The problem of spam e-mail has gained a tremendous amount of attention. Although entities tend to use e-mail spam filter applications to filter out received spam e-mails, marketing companies still tend to send unsolicited emails in bulk and users still receive a reasonable amount of spam e-mail despite those filtering applications. This work proposes a new method for classifying emails into spa...

The locally linear embedding (LLE) algorithm can be used to discover a low-dimensional subspace from face manifolds. However, it does not mean that a good accuracy can be obtained when classifiers work under the subspace. Based on the proposed ULLELDA (Unified LLE and linear discriminant analysis) algorithm, an ensemble version of the ULLELDA (En-ULLELDA) is proposed by perturbing the neighbor ...

Melanoma is the most dangerous skin cancer and early diagnosis is the key factor in its successful treatment. Experienced dermatologists with specific training make the diagnosis by clinical inspection and they reach 80% level of both sensitivity and specificity. In this paper, we present MEDS (MElanoma Diagnosis System): a knowledge-based system for supporting the early diagnosis of melanoma, ...