Analysis of Deep Learning-Based Object Detection Across Infrared Bands for UAV Imagery in Military Applications

Yusuf Furkan Yücesoy; Çağrı Şahin

doi:10.54287/gujsa.1905999

Analysis of Deep Learning-Based Object Detection Across Infrared Bands for UAV Imagery in Military Applications

Abstract

In modern military operations, object detection plays an important role in enhancing situational awareness and tactical decision-making. However, the use of object detection in complex military environments faces challenges, including poor visibility and the need for real-time decision-making. Infrared imaging technologies, which operate outside the visible spectrum, are effective for detecting military targets, particularly in low-visibility conditions. Despite the advantages of infrared imaging for object detection, comparison of performance across different infrared spectra in military applications remains limited. This limitation is primarily due to the varying object visibility across different infrared bands and the lack of accessible military datasets, which are crucial for analyzing how these bands influence military object detection and the performance of deep learning models under such conditions. This study provides an analysis of object detection across various infrared bands, including near-infrared, short-wavelength infrared, mid-wavelength infrared, and long-wavelength infrared, using popular deep learning-based object detection models such as YOLOv8, YOLOv9, YOLO Ghost P2, and RT-DETR. The models were trained separately on each infrared band using simulated data and evaluated for their ability to recognize military tanks, as this capability is crucial for unmanned aerial vehicles in modern defense applications. Our findings reveal that the near-infrared band is the most suitable for detecting tanks, and the YOLOv8 model provides the best performance.

Keywords

References

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Details

Primary Language

English

Subjects

Image Processing, Deep Learning, Computer System Software

Journal Section

Research Article

Authors

Yusuf Furkan Yücesoy
0009-0000-0204-2560
Türkiye

Çağrı Şahin ^*
0000-0001-5800-6243
Türkiye

Publication Date

June 30, 2026

Submission Date

March 9, 2026

Acceptance Date

June 5, 2026

Published in Issue

Year 2026 Volume: 13 Number: 2

DOI

https://doi.org/10.54287/gujsa.1905999

IZ

https://izlik.org/JA32BA46XN

Cite

RIS / Bibtex

APA

Yücesoy, Y. F., & Şahin, Ç. (2026). Analysis of Deep Learning-Based Object Detection Across Infrared Bands for UAV Imagery in Military Applications. Gazi University Journal of Science Part A: Engineering and Innovation, 13(2), 710-732. https://doi.org/10.54287/gujsa.1905999

AMA

1.Yücesoy YF, Şahin Ç. Analysis of Deep Learning-Based Object Detection Across Infrared Bands for UAV Imagery in Military Applications. GU J Sci, Part A. 2026;13(2):710-732. doi:10.54287/gujsa.1905999

Chicago

Yücesoy, Yusuf Furkan, and Çağrı Şahin. 2026. “Analysis of Deep Learning-Based Object Detection Across Infrared Bands for UAV Imagery in Military Applications”. Gazi University Journal of Science Part A: Engineering and Innovation 13 (2): 710-32. https://doi.org/10.54287/gujsa.1905999.

EndNote

Yücesoy YF, Şahin Ç (June 1, 2026) Analysis of Deep Learning-Based Object Detection Across Infrared Bands for UAV Imagery in Military Applications. Gazi University Journal of Science Part A: Engineering and Innovation 13 2 710–732.

IEEE

[1]Y. F. Yücesoy and Ç. Şahin, “Analysis of Deep Learning-Based Object Detection Across Infrared Bands for UAV Imagery in Military Applications”, GU J Sci, Part A, vol. 13, no. 2, pp. 710–732, June 2026, doi: 10.54287/gujsa.1905999.

ISNAD

Yücesoy, Yusuf Furkan - Şahin, Çağrı. “Analysis of Deep Learning-Based Object Detection Across Infrared Bands for UAV Imagery in Military Applications”. Gazi University Journal of Science Part A: Engineering and Innovation 13/2 (June 1, 2026): 710-732. https://doi.org/10.54287/gujsa.1905999.

JAMA

1.Yücesoy YF, Şahin Ç. Analysis of Deep Learning-Based Object Detection Across Infrared Bands for UAV Imagery in Military Applications. GU J Sci, Part A. 2026;13:710–732.

MLA

Yücesoy, Yusuf Furkan, and Çağrı Şahin. “Analysis of Deep Learning-Based Object Detection Across Infrared Bands for UAV Imagery in Military Applications”. Gazi University Journal of Science Part A: Engineering and Innovation, vol. 13, no. 2, June 2026, pp. 710-32, doi:10.54287/gujsa.1905999.

Vancouver

1.Yusuf Furkan Yücesoy, Çağrı Şahin. Analysis of Deep Learning-Based Object Detection Across Infrared Bands for UAV Imagery in Military Applications. GU J Sci, Part A. 2026 Jun. 1;13(2):710-32. doi:10.54287/gujsa.1905999