ABOUT HRPLANES

High Resolution Planes (HRPlanes) is a novel airplane detection dataset using images from Google Earth (GE). We have downloaded 4800 x 2703 sized 3092 RGB images from the biggest airports of the world such as Paris-Charles de Gaulle, John F. Kennedy, Frankfurt, Istanbul, Madrid, Dallas, Las Vegas and Amsterdam Airports and aircraft boneyards like Davis-Monthan Air Force Base. Dataset images were annotated manually by creating bounding boxes for each airplane using formerly HyperLabel software. Quality control of each label was conducted by visual inspection of independent analysts who were not included in the labelling procedure. A total of 18,477 airplanes have been labelled. The provided annotations are in YOLO format. The dataset has been approximately split as 70% (2170 images), 20% (620 images) and 10% (311 images) for training, validation and testing, respectively.

CITATION

If you make use of the test dataset or weights, please cite our paper.

Bakırman, T. & Sertel, E. (2023). "A benchmark dataset for deep learning-based airplane detection: HRPlanes". International Journal of Engineering and Geosciences, 8 (3), 212-223. DOI: 10.26833/ijeg.1107890.