Search results

Filters

  • Journals
  • Authors
  • Keywords
  • Date
  • Type

Search results

Number of results: 2
items per page: 25 50 75
Sort by:
Download PDF Download RIS Download Bibtex

Abstract

Today’s human-computer interaction systems have a broad variety of applications in which automatic human emotion recognition is of great interest. Literature contains many different, more or less successful forms of these systems. This work emerged as an attempt to clarify which speech features are the most informative, which classification structure is the most convenient for this type of tasks, and the degree to which the results are influenced by database size, quality and cultural characteristic of a language. The research is presented as the case study on Slavic languages.

Go to article

Authors and Affiliations

Željko Nedeljković
Milana Milošević
Željko Đurović
Download PDF Download RIS Download Bibtex

Abstract

The work proposes a new method for vehicle classification, which allows treating vehicles uniformly at the stage of defining the vehicle classes, as well as during the classification itself and the assessment of its correctness. The sole source of information about a vehicle is its magnetic signature normalised with respect to the amplitude and duration. The proposed method allows defining a large number (even several thousand) of classes comprising vehicles whose magnetic signatures are similar according to the assumed criterion with precisely determined degree of similarity. The decision about the degree of similarity and, consequently, about the number of classes, is taken by a user depending on the classification purpose. An additional advantage of the proposed solution is the automated defining of vehicle classes for the given degree of similarity between signatures determined by a user. Thus the human factor, which plays a significant role in currently used methods, has been removed from the classification process at the stage of defining vehicle classes. The efficiency of the proposed approach to the vehicle classification problem was demonstrated on the basis of a large set of experimental data.

Go to article

Authors and Affiliations

J. Gajda
M. Mielczarek

This page uses 'cookies'. Learn more