Sequential classifier combination for pattern recognition in wireless sensor networks

Janos Csirik, Peter Bertholet, Horst Bunke

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In the current paper we consider the task of object classification in wireless sensor networks. Due to restricted battery capacity, minimizing the energy consumption is a main concern in wireless sensor networks. Assuming that each feature needed for classification is acquired by a sensor, a sequential classifier combination approach is proposed that aims at minimizing the number of features used for classification while maintaining a given correct classification rate. In experiments with data from the UCI repository, the feasibility of this approach is demonstrated.

Original languageEnglish
Title of host publicationMultiple Classifier Systems - 10th International Workshop, MCS 2011, Proceedings
Pages187-196
Number of pages10
DOIs
Publication statusPublished - Sep 26 2011
Event10th International Workshop on Multiple Classifier Systems, MCS 2011 - Naples, Italy
Duration: Jun 15 2011Jun 17 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6713 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other10th International Workshop on Multiple Classifier Systems, MCS 2011
CountryItaly
CityNaples
Period6/15/116/17/11

Keywords

  • Sequential classifier combination
  • feature ranking
  • feature selection
  • system lifetime
  • wireless sensor networks

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Csirik, J., Bertholet, P., & Bunke, H. (2011). Sequential classifier combination for pattern recognition in wireless sensor networks. In Multiple Classifier Systems - 10th International Workshop, MCS 2011, Proceedings (pp. 187-196). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6713 LNCS). https://doi.org/10.1007/978-3-642-21557-5_21