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2021 IEEE/AIAA 40th Digital Avionics Systems Conference (DASC)
We present a convolutional neural network model that correctly identifies drone models in real-life video streams of flying drones. To achieve this, we show a method of generating synthetic drone images. To create a diverse dataset, the simulation parameters (such as drone textures, lighting, and orientation) are randomized. This synthetic dataset is used to train a convolutional neural network to identify the drone model: DJI Phantom, DJI Mavic, or DJI Inspire. The model is then tested on adoi:10.1109/dasc52595.2021.9594392 fatcat:4tii4kmlyjah7pyru3eqwklxxa