Cover
Vol. 21 No. 2 (2025)

Published: December 16, 2025

Pages: 216-236

Review Article

A Comprehensive Review for Aircraft Detection Techniques Utilizing Deep Learning

Marwa Hameed 1 Zainab Khalaf 2
1Department of Computer Science, College of Computer Science & Information Technology, Basrah University, Basrah,Iraq
2Department of Computer Science, College of Education for Pure Sciences, Basrah University, Basrah, Iraq
History
  • Received: January 20, 2024
  • Revised: June 7, 2024
  • Accepted: June 9, 2024
  • Available Online: February 28, 2025
DOI

https://doi.org/10.37917/ijeee.21.2.21

Abstract

Aircraft detection is a vital and significant field within object detection that has garnered considerable attention from academics, particularly following the advancement of deep learning methods. Aircraft detection has recently become widely utilized in several civil and military fields. This comprehensive survey meticulously categorizes and evaluates diverse deep learning methodologies in airplane detection research. Encompassing radar-based, image-based, and multimodal approaches, the paper presents a structured framework to enhance understanding of the evolving research landscape within this domain. The survey critically identifies gaps and discerns emerging trends, offering valuable insights into standard datasets of aircraft images, performance metrics, real-world applications, and challenges and limitations encountered by aircraft detection systems. Its potential contributions are underscored as pivotal for advancing the safety and security of air travel. This research paper is the inaugural publication of its kind in the domain of aircraft detection review papers, establishing itself as an all-encompassing reference for subsequent scholars.

Keywords

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