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DOI: 10.14569/IJACSA.2022.01305111
PDF

End-to-End Car Make and Model Classification using Compound Scaling and Transfer Learning

Author 1: Omar BOURJA
Author 2: Abdelilah MAACH
Author 3: Zineb ZANNOUTI
Author 4: Hatim DERROUZ
Author 5: Hamza MEKHZOUM
Author 6: Hamd AIT ABDELALI
Author 7: Rachid OULAD HAJ THAMI
Author 8: Francois BOURZEIX

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 5, 2022.

  • Abstract and Keywords
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Abstract: Recently, Morocco has started to invest in IoT systems to transform our cities into smart cities that will promote economic growth and make life easier for citizens. One of the most vital addition is intelligent transportation systems which represent the foundation of a smart city. However, the problem often faced in such systems is the recognition of entities, in our case, car and model makes. This paper proposes an approach that identifies makes and models for cars using transfer learning and a workflow that first enhances image quality and quantity by data augmentation and then feeds the newly generated data into a deep learning model with a scaling feature–that is, compound scaling. In addition, we developed a web interface using the FLASK API to make real-time predictions. The results obtained were 80%accuracy, fine-tuning it to an accuracy rate of 90% on unseen data. Our framework is trained on the commonly used Stanford Cars dataset.

Keywords: Vehicles classification; deep learning; compound scaling; transfer learning; IoT

Omar BOURJA, Abdelilah MAACH, Zineb ZANNOUTI, Hatim DERROUZ, Hamza MEKHZOUM, Hamd AIT ABDELALI, Rachid OULAD HAJ THAMI and Francois BOURZEIX, “End-to-End Car Make and Model Classification using Compound Scaling and Transfer Learning” International Journal of Advanced Computer Science and Applications(IJACSA), 13(5), 2022. http://dx.doi.org/10.14569/IJACSA.2022.01305111

@article{BOURJA2022,
title = {End-to-End Car Make and Model Classification using Compound Scaling and Transfer Learning},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.01305111},
url = {http://dx.doi.org/10.14569/IJACSA.2022.01305111},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {5},
author = {Omar BOURJA and Abdelilah MAACH and Zineb ZANNOUTI and Hatim DERROUZ and Hamza MEKHZOUM and Hamd AIT ABDELALI and Rachid OULAD HAJ THAMI and Francois BOURZEIX}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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