Sequential Classifier Combination for Pattern Recognition in Wireless Sensor Networks

  • Janos Csirik
  • Peter Bertholet
  • Horst Bunke
Conference paper

DOI: 10.1007/978-3-642-21557-5_21

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6713)
Cite this paper as:
Csirik J., Bertholet P., Bunke H. (2011) Sequential Classifier Combination for Pattern Recognition in Wireless Sensor Networks. In: Sansone C., Kittler J., Roli F. (eds) Multiple Classifier Systems. MCS 2011. Lecture Notes in Computer Science, vol 6713. Springer, Berlin, Heidelberg

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.

Keywords

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

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Janos Csirik
    • 1
  • Peter Bertholet
    • 2
  • Horst Bunke
    • 2
  1. 1.Institute of InformaticsUniversity of SzegedHungary
  2. 2.Institute of Informatics and Applied MathematicsUniversity of BernSwitzerland

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