Handwriting Recognition Methods and Approaches

dc.contributor.author	Bodnia, Yevhen
dc.contributor.author	Kozulia, Mariia
dc.date.accessioned	2024-02-15T19:23:59Z
dc.date.available	2024-02-15T19:23:59Z
dc.date.issued	2020
dc.description.abstract	The 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.citation	Bodnia Y. Handwriting Recognition Methods and Approaches [Electronic resource] / Y. Bodnia, M. Kozulia // Computational Linguistics and Intelligent Systems (COLINS 2020) : proc. of the 4th Intern. Conf., April 23-24, 2020. Vol. 2. – Electronic text data. – Lviv, 2020. – P. 251-253. – Access mode: https://colins.in.ua/wp-content/uploads/2020/06/preface_colins_volume2_2020_part6.pdf, free (date of the application 15.02.2024.).
dc.identifier.uri	https://repository.kpi.kharkov.ua/handle/KhPI-Press/74155
dc.language.iso	en
dc.subject	character recognition
dc.subject	neural network
dc.subject	recognition methods
dc.subject	convolutional network
dc.subject	data models
dc.title	Handwriting Recognition Methods and Approaches
dc.type	Article

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