A New Convolutional Neural Network for Recognizing Handwritten Letters of the Russian Alphabet

被引：1

作者：

Safonova, Anastasiia ^{[1
]}

Levkov, Andrey ^{[2
]}

Kaplun, Dmitry ^{[1
]}

机构：

[1] St Petersburg Electrotech Univ LETI, Dept Automat & Control Proc, St Petersburg, Russia

[2] Siberian Fed Univ, Inst Space & Informat Technol, Krasnoyarsk, Russia

来源：

2022 45TH INTERNATIONAL CONFERENCE ON TELECOMMUNICATIONS AND SIGNAL PROCESSING, TSP | 2022年

关键词：

convolutional neural network; image processing; letters of the Russian alphabet; recognition;

D O I：

10.1109/TSP55681.2022.9851369

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

With the rapid development of computer technology, it is becoming increasingly important to have the ability to convert handwritten text into a digital version of printed text for copying, editing, or extracting data from it. The first stage of this process is the recognition of the letters of the proposed text. The article presents a new convolutional neural network (CNN) for image recognition of handwritten letters of the Russian alphabet. The resulting CNN algorithm transforms the image and recognizes the letter that is depicted on it. The final classification accuracy of the NN model on an independent dataset reaches up to 99%.

引用

页码：272 / 275

页数：4

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