Object Detection Using Deep Learning Methods: A Review

Authors

• Asmaa Hasan Alrubaie, Computer Science Department, University of Technology, Baghdad, IraqFollow
• Maisa'a Abid Ali, Computer Engineering Department, University of Technology, IraqFollow
• Ahmed Talib Abdulameer, IT Department, Technical College of Management, Middle Technical University, Baghdad, IraqFollow

Document Type

Review

Keywords

Computer Engineering

Abstract

Target detection, one of the key functions of computer vision, has grown in importance as a study area over the past two decades and is currently often employed. In a certain video, it seeks to rapidly and precisely detect and locate a huge amount of the objects according to redetermined categories. The two forms of deep learning (DL) algorithms that are used in the model training algorithm are single-stage and 2-stage algorithms of detection. The representative algorithms for every level have been thoroughly discussed in this work. The analysis and comparison of numerous representative algorithms in this subject is after that explained. Last but not least, potential obstacles to target detection are anticipated.

How to Cite This Article

Alrubaie, Asmaa Hasan; Abid Ali, Maisa'a; and Abdulameer, Ahmed Talib (2023) "Object Detection Using Deep Learning Methods: A Review," Iraqi Journal of Computers, Communications, Control and Systems Engineering: Vol. 23: Iss. 2, Article 11.
DOI: 10.33103/uot.ijccce.23.2.11
Available at: https://ijccce.researchcommons.org/journal/vol23/iss2/11