preprintarXiv (Cornell University)Jun 9, 2014GREEN OA

Synthetic Data and Artificial Neural Networks for Natural Scene Text Recognition

University of Oxford

Indexed inarxivdatacite

Abstract

In this work we present a framework for the recognition of natural scene text. Our framework does not require any human-labelled data, and performs word recognition on the whole image holistically, departing from the character based recognition systems of the past. The deep neural network models at the centre of this framework are trained solely on data produced by a synthetic text generation engine -- synthetic data that is highly realistic and sufficient to replace real data, giving us infinite amounts of training data. This excess of data exposes new possibilities for word recognition models, and here we consider three models, each one "reading" words in a different way: via 90k-way dictionary encoding,…

Citation impact

809
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32
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Authors

4

Topics & keywords

Keywords
  • Computer science
  • Word (group theory)
  • Encoding (memory)
  • Artificial neural network
  • Character (mathematics)
  • Artificial intelligence
  • Reading (process)
  • Natural language processing
UN Sustainable Development Goals
  • Quality Education
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