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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.

Comments

This article was published digitally by Sage Publications ahead of inclusion in an issue of JDMS.

The work is accessible by subscription through the DOI link below.

Source Publication

The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology

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