Authors: Gaikwad Komal Vitthal, Shaikh Javed Ahmad, Shaikh Aslam Amir
Abstract: The detection and Classification of military aircraft play a crucial role in modern defence and surveillance systems. Traditional radar based approaches are often limited by high cost, environmental constraint, and reduced effectiveness against stealth aircraft. This paper presents a deep learning based approach for automatic military aircraft detection using the YOLOv5 object detection framework. The model is trained on publicly available framework. Experimental results demonstrate that the proposed system successfully detects aircraft such as F-35 and F-16 with confidence score of 0.94 and 0.80, respectively, while achieving an inference speed of approximately 6ms per image. The system provides high accuracy,robustness, and real time capability, Making it suitable for defence surveillance applications.
DOI: https://doi.org/10.5281/zenodo.20155776
