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System for Identifying Texts Written in Kazakh Language

Authors: Absenova B.M; Zhanibay S.B; Zheksebay D.M; Temesheva S.A; Turmaganbet U.K;

System for Identifying Texts Written in Kazakh Language

Abstract

Recently, image-based text extraction has becomea prominent and hard study subject in computer vision. In this article, the texts written in Kazakh are classified based on factors such as writing style and diversity of writing, and a text recognition system based on correctly defined terms is developed.Text matching is accomplished by using the EasyOCR library to the input picture to extract the areas containing the words. The words in the text are then determined using the locations acquired. To initialize the text and recognize the defined text, twodistinct functions are utilized. As a consequence, a method for recognizing Kazakh words as graphics is developed. The accuracy of proper text identification revealed a result of 91%.

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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