CYRILLIC HANDWRITTEN OPTICAL CHARACTER RECOGNITION: A REVIEW OF VARIOUS RECOGNITION METHODS

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Date

2022

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Journal ISSN

Volume Title

Publisher

2022 International Young Scholars' Conference

Abstract

Abstract In the age of digital technologies, to simplify the search and storage of information, the translation of handwritten documents into electronic format is an urgent task. Optical character recognition makes it possible to recognize characters from images and scans of documents with subsequent translation into a machine-readable format. At the moment, there are a lot of methods and algorithms of machine learning and computer vision that differ from each other in efficiency and method of application. In many ways, the results of the methods used differ due to the specifics of each language under study, expressed in the difference in the number and type of symbols. The purpose of this review article is to summarize the research conducted in recognizing handwritten Cyrillic characters and to conduct comparative results on methods and their results. As the data under study, we summarized and analyzed research articles on the topic of recognition of Cyrillic handwritten text.

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Keywords

OCR, Handwritten Text Recognition, Neural Networks, Neural Networks, CNN, 2022 International Young Scholars' Conference, №11

Citation

M. Kalken , R. Jantayev / CYRILLIC HANDWRITTEN OPTICAL CHARACTER RECOGNITION: A REVIEW OF VARIOUS RECOGNITION METHODS / 2022 International Young Scholars' Conference