Handwritten character recognition models based on convolutional neural networks

Pomazan, V.; Tvoroshenko, I.; Gorokhovatskyi, V.

Публікація:
Handwritten character recognition models based on convolutional neural networks

dc.contributor.author	Pomazan, V.
dc.contributor.author	Tvoroshenko, I.
dc.contributor.author	Gorokhovatskyi, V.
dc.date.accessioned	2023-09-30T09:02:55Z
dc.date.available	2023-09-30T09:02:55Z
dc.date.issued	2023
dc.description.abstract	This paper explores the possibility of using various convolutional neural network models to recognize handwritten Arabic characters. It discusses which of the existing convolutional neural network models best suits this task. The results are analyzed based on which conclusions are drawn regarding the effectiveness or ineffectiveness of specific convolutional neural network models. The paper provides an analysis of the efficiency of convolutional neural network models for the task of recognizing handwritten Arabic characters.
dc.identifier.citation	Pomazan V. Handwritten character recognition models based on convolutional neural networks / Pomazan V., Tvoroshenko I., and Gorokhovatskyi V. // International Journal of Academic Engineering Research. – 7(9). – pp. 64-72.
dc.identifier.other	http://ijeais.org/wp-content/uploads/2023/9/IJAAR230908.pdf
dc.identifier.uri	https://openarchive.nure.ua/handle/document/24332
dc.language.iso	en_US
dc.publisher	International Journal of Academic Engineering Research
dc.subject	Arabic symbol recognition
dc.subject	computer vision
dc.subject	convolutional neural networks (CNN)
dc.subject	machine learning
dc.subject	symbol recognition
dc.title	Handwritten character recognition models based on convolutional neural networks
dc.type	Article
dspace.entity.type	Publication