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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| Date: | 2021 |
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| Main Authors: | , |
| Format: | Article |
| Language: | English |
| Published: |
Інститут кібернетики ім. В.М. Глушкова НАН України
2021
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| Series: | Кібернетика та комп’ютерні технології |
| Subjects: | |
| Online Access: | https://nasplib.isofts.kiev.ua/handle/123456789/181351 |
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| Journal Title: | Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| Cite this: | 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| Summary: | 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. |
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