Aircraft detection from satellite imagery using synthetic data
Document Type
Article
Publication Date
1-3-2024
Abstract
Excerpt: This paper explores the advancement of object detection models within the domain of satellite imagery analysis, focusing on the innovative application of synthetically generated datasets to enhance model performance. Motivated by the inherent challenges of manual dataset annotation, such as errors, limited variability, and geographical biases, this study employs synthetic data generation techniques to create a diverse dataset by overlaying 3D models of 31 different aircraft types onto satellite imagery, creating a dataset of 5000 images containing 27,375 aircraft.
Source Publication
The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology
Recommended Citation
Everman, R., Wagner, T., Ranly, N., & Cox, B. (2025). Aircraft detection from satellite imagery using synthetic data. The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology, 15485129241309656. https://doi.org/10.1177/15485129241309657
Comments
This article was published digitally by Sage Publications ahead of inclusion in an issue of JDMS.
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