TELKOMNIKA Telecommunication, Computing, Electronics and Control
Official logo recognition based on multilayer convolutional neural network model
Dublin Core
Title
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Official logo recognition based on multilayer convolutional neural network model
Official logo recognition based on multilayer convolutional neural network model
Subject
CNN, Deep learning, Features extraction, Learning, Logo recognition
Description
Deep learning has gained high popularity in the field of image processing
and computer vision applications due to its unique feature extraction
property. For this characteristic, deep learning networks used to solve
different issues in computer vision applications. In this paper the issue has been raised is classification of logo of formal directors in Iraqi government. The paper proposes a multi-layer convolutional neural network (CNN) to classify and recognize these official logos by train the CNN model on several logos. The experimental show the effectiveness of the proposed method to recognize the logo with high accuracy rate about 99.16%. The proposed multi-layers CNN model proves the effectiveness to classify different logos with various conditions.
and computer vision applications due to its unique feature extraction
property. For this characteristic, deep learning networks used to solve
different issues in computer vision applications. In this paper the issue has been raised is classification of logo of formal directors in Iraqi government. The paper proposes a multi-layer convolutional neural network (CNN) to classify and recognize these official logos by train the CNN model on several logos. The experimental show the effectiveness of the proposed method to recognize the logo with high accuracy rate about 99.16%. The proposed multi-layers CNN model proves the effectiveness to classify different logos with various conditions.
Creator
Zahraa Najm Abdullah, Zinah Abdulridha Abutiheen, Ashwan A. Abdulmunem, Zahraa A. Harjan
Source
DOI: 10.12928/TELKOMNIKA.v20i5.23464
Publisher
Universitas Ahmad Dahlan
Date
October 2022
Contributor
Sri Wahyuni
Rights
ISSN: 1693-6930
Relation
http://journal.uad.ac.id/index.php/TELKOMNIKA
Format
PDF
Language
English
Type
Text
Coverage
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Files
Collection
Citation
Zahraa Najm Abdullah, Zinah Abdulridha Abutiheen, Ashwan A. Abdulmunem, Zahraa A. Harjan, “TELKOMNIKA Telecommunication, Computing, Electronics and Control
Official logo recognition based on multilayer convolutional neural network model,” Repository Horizon University Indonesia, accessed September 20, 2024, https://repository.horizon.ac.id/items/show/4423.
Official logo recognition based on multilayer convolutional neural network model,” Repository Horizon University Indonesia, accessed September 20, 2024, https://repository.horizon.ac.id/items/show/4423.