Comparative Analysis of the Application of Multilayer and Convolutional Neural Networks for Recognition of Handwritten Letters of the Azerbaijani Alphabet

The implementation of information technologies in various spheres of public life dictates the creation of efficient and productive systems for entering information into computer systems. In such systems it is important to build an effective recognition module. At the moment, the most effective metho...

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Збережено в:
Бібліографічні деталі
Дата:2021
Автори: Mustafayev, E., Azimov, R.
Формат: Стаття
Мова:English
Опубліковано: Інститут кібернетики ім. В.М. Глушкова НАН України 2021
Назва видання:Кібернетика та комп’ютерні технології
Теми:
Онлайн доступ:https://nasplib.isofts.kiev.ua/handle/123456789/181351
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Назва журналу:Digital Library of Periodicals of National Academy of Sciences of Ukraine
Цитувати:Comparative Analysis of the Application of Multilayer and Convolutional Neural Networks for Recognition of Handwritten Letters of the Azerbaijani Alphabet / E. Mustafayev, R. Azimov // Кібернетика та комп’ютерні технології: Зб. наук. пр. — 2021. — № 3. — С. 65-73. — Бібліогр.: 13 назв. — англ.

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Digital Library of Periodicals of National Academy of Sciences of Ukraine
Опис
Резюме:The implementation of information technologies in various spheres of public life dictates the creation of efficient and productive systems for entering information into computer systems. In such systems it is important to build an effective recognition module. At the moment, the most effective method for solving this prob-lem is the use of artificial multilayer neural and convolutional networks. This paper is devoted to a comparative analysis of the recognition results of handwritten characters of the Azerbaijani al-phabet using neural and convolutional neural networks. The results of numerical experiments are given.