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Attention Improves the Recognition Reliability of Backpropagation Network

  • Zbigniew Mikrut
  • Agata Piaskowska
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4029)

Abstract

In the paper a method is presented for improving the recognition reliability of backpropagation-type networks, based on the attention shifting technique. The mechanism is turned on in cases when the reliability of the network’s answer is low. The signals reaching the hidden layer are used for selection of image areas which are the most ”doubtful” in the process of recognition by the network. Three methods have been proposed for appending the input vector after shifting the area where the attention is focused. The methods have been tested in the problem of hand-written digits recognition. Noticeable improvement of the recognition reliability has been obtained.

Keywords

Hide Layer Recognition Rate Bicubic Interpolation Handwritten Digit Recognition Recognition Reliability 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Zbigniew Mikrut
    • 1
  • Agata Piaskowska
    • 1
  1. 1.Institute of AutomaticsAGH University of Science and TechnologyKrakowPoland

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