Combining Neural Networks to Improve Performance of Handwritten Keyword Spotting

  • Volkmar Frinken
  • Andreas Fischer
  • Horst Bunke
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5997)

Abstract

Keyword spotting refers to the process of retrieving all instances of a given word in a document. It has received significant amounts of attention recently as an attractive alternative to full text transcription, and is particularly suited for tasks such as document searching and browsing. In the present paper we propose a combination of several keyword spotting systems for unconstrained handwritten text. The individual systems are based on a novel type of neural network. Due to their random initialization, a great variety in performance is observed among the neural networks. We demonstrate that by using a combination of several networks the best individual system can be outperformed.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Volkmar Frinken
    • 1
  • Andreas Fischer
    • 1
  • Horst Bunke
    • 1
  1. 1.Institute of Computer Science and Applied MathematicsUniversity of BernBernSwitzerland

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