BOOK-CHAPTER

Handwritten character recognition using machine learning and deep learning

Abstract

Digitisation of machines has been facilitating humans in all possible ways yet imaginable, an approach to make the automation for recognising the patterns and characters in the media and document is also advancing in the field. The science that enables us to transform data from any type of document or image file for analysing, editing or searching purpose is optical character recognition. A very prominent part within the Optical Character Recognition technology sphere is Handwriting character recognition. Though it cannot be denied that practical application of handwriting recognition is a complex process, yet it is of a great use, especially in fields that still take written documents into consideration for formal and verification purposes. Among all the possible technologies and methodologies available till the date, machine learning and deep learning techniques are considered to be the most efficient and useful for optical character recognition work. The following research paper is prepared by taking into account numerous sites, documents, articles and research papers from sites like Google scholar and IEEE published research papers in the field of Optical Character Recognition.

Keywords:
Artificial intelligence Character (mathematics) Computer science Character recognition Deep learning Pattern recognition (psychology) Speech recognition Natural language processing Mathematics

Metrics

4
Cited By
2.14
FWCI (Field Weighted Citation Impact)
0
Refs
0.89
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Handwritten Text Recognition Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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