66 citations · 159 across the 5 of their papers we have counts for
5 papers
Machine Learning Applications to Kronian Magnetospheric Reconnection Classification
Tadhg M. Garton, Caitriona M. Jackman, Andy W. Smith +3
The products of magnetic reconnection in Saturn's magnetotail are identified in magnetometer observations primarily through characteristic deviations in the north-south component o…
The Observational Uncertainty of Coronal Hole Boundaries in Automated Detection Schemes
Martin A. Reiss, Karin Muglach, Christian Möstl +16
Coronal holes are the observational manifestation of the solar magnetic field open to the heliosphere and are of pivotal importance for our understanding of the origin and accelera…
Integrating Machine Learning for Planetary Science: Perspectives for the Next Decade
Abigail R. Azari, John B. Biersteker, Ryan M. Dewey +13
Machine learning (ML) methods can expand our ability to construct, and draw insight from large datasets. Despite the increasing volume of planetary observations, our field has seen…
Expansion of High Speed Solar Wind Streams from Coronal Holes through the Inner Heliosphere
Tadhg M. Garton, Sophie A. Murray, Peter T. Gallagher
Coronal holes (CHs) are regions of open magnetic flux which are the source of high speed solar wind (HSSW) streams. To date, it is not clear which aspects of CHs are of most influe…
Automated Coronal Hole Identification via Multi-Thermal Intensity Segmentation
Tadhg M. Garton, Peter T. Gallagher, Sophie A. Murray
Coronal holes (CH) are regions of open magnetic fields that appear as dark areas in the solar corona due to their low density and temperature compared to the surrounding quiet coro…