Comparative Analysis of the Application of Multilayer and Convolutional Neural Networks for Recognition of Handwritten Letters of the Azerbaijani Alphabet
Introduction. 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 e...
Main Authors: | Elshan Mustafayev, Rustam Azimov |
---|---|
Format: | Article |
Language: | English |
Published: |
V.M. Glushkov Institute of Cybernetics
2021-09-01
|
Series: | Кібернетика та комп'ютерні технології |
Subjects: | |
Online Access: | http://cctech.org.ua/13-vertikalnoe-menyu-en/281-abstract-21-3-6-arte |
Similar Items
-
Improved Handwritten Digit Recognition Using Convolutional Neural Networks (CNN)
by: Savita Ahlawat, et al.
Published: (2020-06-01) -
Latin Letters Recognition Using Optical Character Recognition to Convert Printed Media Into Digital Format
by: Rio Anugrah, et al.
Published: (2017-12-01) -
Handwritten Arabic Character Recognition for Children Writing Using Convolutional Neural Network and Stroke Identification
by: Mais Alheraki, et al.
Published: (2023-05-01) -
Handwritten Character Recognition to Obtain Editable Text
by: Pravalika Jella, et al.
Published: (2023-01-01) -
Offline Handwritten English Alphabet Recognition (OHEAR)
by: Hamsa D. Majeed, et al.
Published: (2022-08-01)