Using Game Engines and Machine Learning to Create Synthetic Satellite Imagery for a Tabletop Verification Exercise

arXiv:2404.11461v1 Announce Type: new
Abstract: Satellite imagery is regarded as a great opportunity for citizen-based monitoring of activities of interest. Relevant imagery may however not be available at sufficiently high resolution, quality, or cadence -- let alone be uniformly accessible to open-source analysts. This limits an assessment of the true long-term potential of citizen-based monitoring of nuclear activities using publicly available satellite imagery. In this article, we demonstrate how modern game engines combined with advanced machine-learning techniques can be used …

abstract analysts arxiv cadence create cs.ai cs.cv cs.hc cs.lg exercise game game engines however machine machine learning monitoring quality resolution satellite synthetic type verification