Using a Convolutional Neural Network for Machine Written Character Recognition

Convolutional neural networks are special types of artificial neural networks that can solve various tasks in computer vision, such as image classification, object detection, and general recognition. The paper presents the basic building blocks of convolutional neural networks and their architecture...

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Bibliographic Details
Published in:TEM Journal 2023-08, Vol.12 (3), p.1252-1259
Main Authors: Karrach, Ladislav, Pivarčiová, Elena
Format: Article
Language:English
Subjects:
Artificial neural networks
Automation
Character recognition
Classification
Computer vision
Configurations
ICT Information and Communications Technologies
Image classification
Information Architecture
Neural networks
Neurons
Object recognition
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Summary:Convolutional neural networks are special types of artificial neural networks that can solve various tasks in computer vision, such as image classification, object detection, and general recognition. The paper presents the basic building blocks of convolutional neural networks and their architecture, and compares their recognition accuracy with other character recognition techniques using the example of character recognition from vehicle registration plates. The purpose of the experiments was to determine the optimal configuration of the convolutional neural network and the influence of the size and design method of the training set on the recognition rate. The study shows that although convolutional neural networks have recently gained attention, traditional recognition methods are still relevant, and the choice of the right classifier and its configuration depends on the type of recognition task.
ISSN:2217-8309
2217-8333
DOI:10.18421/TEM123-03