We propose a new algorithm for pattern recognition that outputs some measures of \reliability" for every prediction made, in contrast to the current algorithms that output \bare" predictions only. Our method uses a rule similar to that of nearest neighbours to infer predictions ; thus its predictive performance is close to that of nearest neighbours, while the measures of conndence it outputs p...

This paper introduces a novel approach for evaluating fabric sensory responses. First, the problems in existing techniques are analyzed, and by comparing with successful cases in assessing human feeling towards cold/warmth and human color sense, a more scientific scheme based on the computer pattern recognition technique is exhibited and the details of the measurements, data processing and calc...

Half away between edge detection and pattern recognition this study aim to characterize singularities in order to build closed edges and to classify object within an image.

In this study, a supervised pattern recognition technique is used to examine Long Term Geoelectric Potential difference (LTGP) data recorded during the 1993-1997 period in Western Greece. It presents initial results from an attempt towards automated discovery of similarities between LTGP data recorded during periods of similar seismic activity. In particular, we investigate whether patterns exi...

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...