articleJan 1, 2024GREEN OA

Reading digits in natural images with unsupervised feature learning

Google (United States)

Indexed indatacite

Abstract

Detecting and reading text from natural images is a hard computer vision task that is central to a variety of emerging applications. Related problems like document character recognition have been widely studied by computer vision and machine learning researchers and are virtually solved for practical applications like reading handwritten digits. Reliably recognizing characters in more complex scenes like photographs, however, is far more difficult: the best existing methods lag well behind human performance on the same tasks. In this paper we attack the problem of recognizing digits in a real application using unsupervised feature learning methods: reading house numbers from street level photos. To this end,…

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Topics & keywords

Keywords
  • Computer science
  • Artificial intelligence
  • Feature (linguistics)
  • Benchmark (surveying)
  • Reading (process)
  • Task (project management)
  • Unsupervised learning
  • Feature learning
UN Sustainable Development Goals
  • Quality Education
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