This paper describes a system called Diamond for interactive exploration of multidimensional data. Diamond takes advantage of human pattern recognition and processing capacity, and puts major emphasis on performance and responsiveness. This creates a highly productive symbiosis between the human and the system. The basic philosophy of Diamond is to depict the data with pictures, and to help the...

Robust pattern recognition within the Bayesian framework for scene segmentation/boundary detection is oftentimes hampered by the presence of textures within natural images. In order to improve segmentation/boundary detection on natural images, it is necessary to combine multiple features eeectively. This paper introduces two algorithms for combining both color and texture features to assist bou...

This document contains a brief presentation of the PRESEMT project that aims in the development of a novel language-independent methodology for the creation of a flexible and adaptable MT system.

In this work we have proposed an innovative and accurate solution for non-technical losses identification using the Optimum-Path Forest (OPF) classifier and its learning algorithm. Results in two datasets demonstrated that OPF outperformed the state of the art pattern recognition techniques and OPF with learning achieved better results for automatic nontechnical losses identification than recen...

Electrons and photons reconstruction and identification is an issue of great importance for many physics analyses at LEP2. The variety of topologies and energy ranges in which they can appear required an improvement of the previous LEP1 pattern recognition. The REMCLU package has been built in order to improve the previous tools for the barrel part of DELPHI, and to provide an efficient general...

The main goal of the paper is to show that commutative hypercomplex algebras and Clifford algebras can be used to solve problems of multicolor image processing and pattern recognition in a natural and effective manner.

The problem of decision functions quality in pattern recognition is considered. An overview of the approaches to the solution of this problem is given. Within the Bayesian framework, we suggest an approach based on the Bayesian interval estimates of quality on a finite set of events.

This paper studies the effect of incipient stator faults in salient-pole synchronous generators and its detection using a simple pattern recognition methodology. A theoretical linear model for the synchronous generator is first developed to provide the relationships between stator and rotor harmonic currents and possible incipient faults on stator electric circuits. All theoretical findings wer...