Propose an Object Detection Optimization Algorithm by Using Particle Swarm Optimization (PSO) Based-on Exploration Ability of Grey Wolf Optimizer (GWO)

Hayder Talib Jawad Al-Sammak
International Journal of Computational and Electronic Aspects in Engineering
Volume 5: Issue 2, June 2024, pp 54-60

Author's Information
Hayder Talib Jawad Al-Sammak 1 
Corresponding Author
1Biomedical Informatics College, University of Information Technology and Communications, Baghdad, Iraq
ht582001@gmail.com
Research Paper -- Peer Research Papered
First online on – 30 June 2024

Open Access article under Creative Commons License

Cite this article –Hayder Talib Jawad Al-Sammak “Propose an Object Detection Optimization Algorithm by Using Particle Swarm Optimization (PSO) Based-on Exploration Ability of Grey Wolf Optimizer (GWO)”, International Journal of Computational and Electronic Aspects in Engineering, RAME Publishers, vol. 5, Issue 2, pp. 54-60, 2024.
https://doi.org/10.26706/ijceae.5.2.20240507

Abstract:-
There are many algorithms that have been designed for the purpose of applying them to the subject of object detection, including Particle Swarm Optimization (PSO), as well as Gray Wolf Optimizer (GWO), and many other algorithms. In this article, I will address the problem of object detection and take advantage of some characteristics of the PSO and GWO algorithms to build an algorithm that is distinguished by the accuracy and browsing of the PSO algorithm, as well as the search speed characteristic provided by the GWO algorithm. The proposed algorithm was called Proposed-Hybrid Optimization (PHO), and a set of functions were defined and three of them were selected to solve the problem of object detection. The accuracy and speed of the results were acceptable and good compared to previous studies that were discussed in a special section.
Index Terms:-
particle swarm optimization (PSO), gray wolf optimizer (GWO), object detection, hybrid optimization.
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