A Comprehensive Review for Aircraft Detection Techniques Utilizing Deep Learning - Hameed, Marwa; Khalaf, Zainab (Iraqi Journal for Electrical and Electronic Engineering, 2025)
Aircraft detection is a vital and significant field within object detection that has garnered considerable attention fromacademics, particularly following the advancement of deep learning methods. Aircraft detection has recently becomewidely utilized in several civil and military fields. This comprehensive survey meticulously categorizes and evaluatesdiverse deep learning methodologies in airplane detection research. Encompassing radar-based, image-based, andmultimodal approaches, the paper presents a structured framework to enhance understanding of the evolving researchlandscape within this domain. The survey critically identifies gaps and discerns emerging trends, offering valuableinsights into standard datasets of aircraft images, performance metrics, real-world applications, and challenges andlimitations encountered by aircraft detection systems. Its potential contributions are underscored as pivotal for advancingthe safety and security of air travel. This research paper is the inaugural publication of its kind in the domain of aircraftdetection review papers, establishing itself as an all-encompassing reference for subsequent scholars.