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Chowdhury, Rajesh KIIT-MiTA Mendeley Data High-Resolution Drone Imagery for Military Object Detection and Recognition About Dataset Drone Images for Military Object Detection This dataset contains 1,700 high-resolution images captured by drones, annotated in the YOLO format for object detection tasks. The images span 7 distinct classes, including: Artilary Missile Radar M. Rocket Launcher Soldier Tank Vehicle 🧩 Key Features Suitable for military and security-focused research. Includes detailed bounding box annotations for each object class. Ideal for training YOLO-based models or other object detection architectures. ⚙️ Usage This dataset is intended for educational and research purposes only. Commercial use is strictly prohibited. If used, proper attribution to the creator is required. 📄 Citation If you use this dataset in your research, please cite the following paper: S. Chakrabarty, R. Chatterjee, S. Chakraborty, S. Roy Shuvo, and R. Chowdhury, "Drones in Defense: Real-Time Vision-Based Military Target Surveillance and Tracking," 2025 3rd International Conference on Intelligent Systems, Advanced Computing and Communication (ISACC), Silchar, India, 2025, pp. 508–513, doi: 10.1109/ISACC65211.2025.10969335 🔗 Paper Link 📘 View on IEEE Xplore ⚠️ Note This dataset was used as part of the above research publication. Please ensure proper citation if you use it in any academic or research work. Computer Vision Object Detection Image Classification Military YOLOv5 Dataset doi:10.17632/drjmrf5kk5.1 oai:data.mendeley.com/drjmrf5kk5.1 Creative Commons Attribution 4.0 International http://creativecommons.org/licenses/by/4.0 https://data.mendeley.com/datasets/drjmrf5kk5 2026-02-23T19:08:34Z