File(s) not publicly available
An application of deep learning in character recognition: an overview
For automated document analysis, OCR (Optical character recognition) is a basic building block. The robust automated document analysis system can have impact over a wider sphere of life. Many of the researchers have been working hard to build OCR systems in various languages with significant degree of accuracy, character recognition rate and minimum error rate. Deep learning is the start of art technique with efficient and accurate result as compared to other techniques. Every language, moreover every script have its own challenges e.g. scripts where characters are well separated are less challenging as compared to cursive scripts where characters are attached with one another. In this chapter, we would take a detailed account of the state of art deep learning techniques for Arabic like script, Latin script and symbolic script.
History
Title of book
Handbook of deep learning applicationsVolume
136Series
Smart innovation, systems and technologiesChapter number
3Pagination
53 - 81Publisher
SpringerPlace of publication
Cham, SwitzerlandPublisher DOI
ISSN
2190-3018eISSN
2190-3026ISBN-13
9783030114794Edition
1stLanguage
engPublication classification
B1.1 Book chapterCopyright notice
2019, Springer Nature Switzerland AG.Extent
17Editor/Contributor(s)
V Balas, S Roy, D Sharma, P SamuiUsage metrics
Categories
No categories selectedKeywords
Licence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC