44 citations · 92 across the 9 of their papers we have counts for
9 papers
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…
First observations of a geomagnetic superstorm with a sub-L1 monitor
Eva Weiler, Christian Möstl, Emma E. Davies +10
Forecasting the geomagnetic effects of solar coronal mass ejections (CMEs) is currently an unsolved problem. CMEs, responsible for the largest values of the north-south component o…
Understanding the effects of spacecraft trajectories through solar coronal mass ejection flux ropes using 3DCOREweb
Hannah Theresa Rüdisser, Andreas Jeffrey Weiss, Justin Le Louëdec +4
This study investigates the impact of spacecraft positioning and trajectory on in situ signatures of coronal mass ejections (CMEs). Employing the 3DCORE model, a 3D flux rope model…
Key Point-based Orientation Estimation of Strawberries for Robotic Fruit Picking
Justin Le Louëdec, Grzegorz Cielniak
Selective robotic harvesting is a promising technological solution to address labour shortages which are affecting modern agriculture in many parts of the world. For an accurate an…
Gaussian map predictions for 3D surface feature localisation and counting
Justin Le Louëdec, Grzegorz Cielniak
In this paper, we propose to employ a Gaussian map representation to estimate precise location and count of 3D surface features, addressing the limitations of state-of-the-art meth…
3D shape sensing and deep learning-based segmentation of strawberries
Justin Le Louëdec, Grzegorz Cielniak
Automation and robotisation of the agricultural sector are seen as a viable solution to socio-economic challenges faced by this industry. This technology often relies on intelligen…
Deep learning investigation for chess player attention prediction using eye-tracking and game data
Justin Le Louedec, Thomas Guntz, James Crowley +1
This article reports on an investigation of the use of convolutional neural networks to predict the visual attention of chess players. The visual attention model described in this…