A MDRNN-SVM Hybrid Model for Cursive Offline Handwriting Recognition

  • Byron Leite Dantas Bezerra
  • Cleber Zanchettin
  • Vinícius Braga de Andrade
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7553)


This paper presents a recurrent neural networks applied to handwriting character recognition. The method Multi-dimensional Recurrent Neural Network is evaluated against classical techniques. To improve the model performance we propose the use of specialized Support Vector Machine combined whit the original Multi-dimensional Recurrent Neural Network in cases of confusion letters. The experiments were performed in the C-Cube database and compared with different classifiers. The hierarchical combination presented promising results.


Support Vector Machine Recognition Rate Recurrent Neural Network Character Recognition Handwriting Recognition 
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© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Byron Leite Dantas Bezerra
    • 1
  • Cleber Zanchettin
    • 2
  • Vinícius Braga de Andrade
    • 1
  1. 1.Polytechnic School of PernambucoUniversity of PernambucoRecifeBrazil
  2. 2.Center of InformaticsFederal University of PernambucoRecifeBrazil

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