Tracking multiple targets in a cluttered environment is a challenging task. Probabilistic multiple hypothesis tracking (PMHT) is an efficient approach for dealing with it. Essentially PMHT is based on expectation-maximization for handling with association conflicts. Linearity in the number of targets and measurements is the main motivation for a further development and extension of this methodo...

Applying a simple and selective sample preparation procedure prior to instrumental analysis is the most important and crucial step in an analytical process. Up to now, various sample preparation techniques based on solid phase extraction (SPE) systems have been developed to isolate various types of analytes from different matrices. In the method presented for preconcentration and measurement of...

Applying a simple and selective sample preparation procedure prior to instrumental analysis is the most important and crucial step in an analytical process. Up to now, various sample preparation techniques based on solid phase extraction (SPE) systems have been developed to isolate various types of analytes from different matrices. In the method presented for preconcentration and measurement of...

Feature selection, representation and extraction are integral to statistical pattern recognition systems. Usually features are represented as vectors that capture expert knowledge of measurable discriminative properties of the classes to be distinguished. The feature selection process entails manual expert involvement and repeated experiments. Automatic feature selection is necessary when (i) e...

The paper studies the problem of analyzing user comments and reviews of products sold online. Analyzing such reviews and producing a summary of them is very useful to both potential customers and product manufacturers. By analyzing reviews, we mean to extract features of products (also called opinion features) that have been commented by reviewers and determine whether the opinions are positive...

The Karhunen-Loeve (KL) transform is an optimal method for approximating a set of vectors or images by a low dimensional subspace. The method provides the optimal partial KL basis, which minimizes the MSE between the given set of vectors and their projections on this basis. In computer vision it is used for a variety of tasks such as object recognition, motion estimation, visual learning and ob...

A classification system typically includes both a feature extractor and a classifier. The two components can be trained either sequentially or simultaneously. The former option has an implementation advantage since the extractor is trained independently of the classifier, but it is hindered by the suboptimality of feature selection. Simultaneous training has the advantage of minimizing classifi...