Deep Computer Vision for Solar Physics Big Data: Opportunities and Challenges
Bo Shen, Marco Marena, Chenyang Li, Qin Li, Haodi Jiang, Mengnan Du, Jiajun Xu, Haimin Wang
TL;DR
An overview of the different types of SPBD is presented, new opportunities in applying deep computer vision to SPBD are explored, the unique challenges are highlighted, and several potential future research directions are outlined.
Abstract
With recent missions such as advanced space-based observatories like the Solar Dynamics Observatory (SDO) and Parker Solar Probe, and ground-based telescopes like the Daniel K. Inouye Solar Telescope (DKIST), the volume, velocity, and variety of data have made solar physics enter a transformative era as solar physics big data (SPBD). With the recent advancement of deep computer vision, there are new opportunities in SPBD for tackling problems that were previously unsolvable. However, there are new challenges arising due to the inherent characteristics of SPBD and deep computer vision models. This vision paper presents an overview of the different types of SPBD, explores new opportunities in applying deep computer vision to SPBD, highlights the unique challenges, and outlines several potential future research directions.