Machine Learning for Handwriting Recognition

  • Preetha S Department of ISE,B.M.S. College of Engineering/ VTU, India, {preetha.ise,1bm16is006, 1bm16is044, 1bm16is060}
  • Afrid I M Department of ISE,B.M.S. College of Engineering/ VTU, India, {preetha.ise,1bm16is006, 1bm16is044, 1bm16is060}
  • Karthik Hebbar P Department of ISE,B.M.S. College of Engineering/ VTU, India, {preetha.ise,1bm16is006, 1bm16is044, 1bm16is060}
  • Nishchay S K Department of ISE,B.M.S. College of Engineering/ VTU, India, {preetha.ise,1bm16is006, 1bm16is044, 1bm16is060}
Keywords: CNN Zoning, Incremental, Handwriting recognition

Abstract

With the knowledge of current data about particular subject, machine learning tries to extract hidden information that lies in the data. By applying some mathematical functions and concepts to extract hidden information, machine learning can be achieved and we can predict output for unknown data. Pattern recognition is one of the main application of ML. Patterns are usually recognized with the help of large image data-set. Handwriting recognition is an application of pattern recognition through image. By using such concepts, we can train computers to read letters and numbers belonging to any language present in an image. There exists several methods by which we can recognize hand-written characters. We will be discussing some of the methods in this paper.

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Published
2020-06-03
How to Cite
S, P., M, A. I., Hebbar P, K., & S K, N. (2020). Machine Learning for Handwriting Recognition. International Journal of Computer (IJC), 38(1), 93-101. Retrieved from https://www.ijcjournal.org/index.php/InternationalJournalOfComputer/article/view/1637
Section
Articles