169 citations · 1.2k across the 34 of their papers we have counts for
3 papers · 1 filter
Predicting CME Arrivals with Heliospheric Imagers from L5: A Data Assimilation Approach
Tanja Amerstorfer, Justin Le Louëdec, David Barnes +5
The Solar TErrestrial RElations Observatory (STEREO) mission has laid a foundation for advancing real-time space weather forecasting by enabling the evaluation of heliospheric imag…
Solar Transient Recognition Using Deep Learning (STRUDL) for heliospheric imager data
Maike Bauer, Justin Le Louëdec, Tanja Amerstorfer +3
Coronal Mass Ejections (CMEs) are space weather phenomena capable of causing significant disruptions to both space- and ground-based infrastructure. The timely and accurate detecti…
Beacon2Science: Enhancing STEREO/HI beacon data with machine learning for efficient CME tracking
Justin Le Louëdec, Maike Bauer, Tanja Amerstorfer +1
Observing and forecasting coronal mass ejections (CME) in real-time is crucial due to the strong geomagnetic storms they can generate that can have a potentially damaging effect, f…