Handwriting recognition methods and approaches

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dc.citation.epage253
dc.citation.spage251
dc.contributor.authorBodnia Yevhen
dc.contributor.authorKozulia Mariia
dc.date.accessioned2022-11-11T08:30:08Z
dc.date.available2022-11-11T08:30:08Z
dc.date.issued2020
dc.description.abstractThe paper analyzes the existing methods and approaches for character recognition. The subject area and its problems are considered. The best method for solving the handwriting recognition task is the convolutional neural network method. Features of software implementation of convolutional neural network, implementation of data storage model for training are considered.
dc.identifier.citationBodnia Ye. Handwriting recognition methods and approaches / Yevhen Bodnia, Mariia Kozulia // Computational Linguistics and Intelligent Systems. – Lviv, 2020. – Volume 2 : Proceedings of the 4nd International conference, COLINS 2020. Workshop, Lviv, Ukraine, June 23–24, 2020. – P. 251–253. – URL: https://colins.in.ua/wp-content/uploads/2020/06/preface_colins_volume2_2020_part6.pdf (дата звернення: 08.11.2022). – Bibliography: 3 titles.
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/57078
dc.language.isoen
dc.publisherонлайн
dc.subjectCharacter recognition, neural network, recognition methods, convolutional network, data models
dc.titleHandwriting recognition methods and approaches
dc.typeConference Abstract

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Computational Linguistics and Intelligent Systems. – 2020 р.