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Aerial Object Detection Dataset containing multiple classes of airborne objects including birds, drones, and fighter jets.
This dataset is designed for training and evaluating Computer Vision models for object detection, classification, and aerial surveillance applications.
📊 Dataset Statistics
| Class Name | Count |
|---|---|
| Birds | 578 |
| Drone | 1,843 |
| Fighter Jet | 4,053 |
| Fixed-Wing-Drone | 716 |
| Fixed-Wing-Hybrid-VTOL-Drone | 90 |
| Total | 7,280 |
- Number of classes: 5
- Number of images:
7,280(annotated) - Annotation format: YOLOv8 / COCO JSON
- Minimum resolution: 640×640 px
- File formats: JPG / PNG
🧠 Use Cases
- Real-time aerial object detection and tracking
- Drone & UAV surveillance systems
- Object classification for air traffic monitoring
- Research in autonomous aerial navigation and security
- Training modern detection architectures like YOLOv8, Faster R-CNN, and DETR
YOLO Format
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