Airside Surveillance by Computer Vision in Low-Visibility and Low-Fidelity Environment

What is it about?

Low visibility at airports can cause significant delays and safety risks due to ground delays and runway/taxiway incursions. We propose a computer vision system using deep learning to detect and track aircraft in challenging conditions. The system proves effective on an airport video dataset from Houston airport, enhancing visibility under adverse weather conditions.

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