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Online Handwriting Recognition Using Multi Convolution Neural Networks

  • Dũng Việt Phạm
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7673)

Abstract

This paper presents a library written by C# language for the online handwriting recognition system using UNIPEN-online handwritten training set. The recognition engine based on convolution neural networks and yields recognition rates to 99% to MNIST training set, 97% to UNIPEN’s digit training set (1a), 89% to a collection of 44022 capital letters and digits (1a,1b) and 89% to lower case letters (1c). These networks are combined to create a larger system which can recognize 62 English characters and digits. A proposed handwriting segmentation algorithm is carried out which can extract sentences, words and characters from handwritten text. The characters then are given as the input to the network.

Keywords

artificial intelligent convolution neural network UNIPEN pattern recognition 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Dũng Việt Phạm
    • 1
  1. 1.Computer Network CentreVietnam Maritime UniversityHai Phong cityVietnam

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