Deep Computer Vision for Solar Physics Big Data: Opportunities and Challenges
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.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Physics-Informed Computer Vision: A Review and Perspectives
The incorporation of physical information in machine learning frameworks is opening and transforming many application domains. Here the learning process is augmented through the induction of fundamental knowledge and gov…
Inductive BiasPhysics-informed machine learningSystematic Literature ReviewMagnetogram-to-Magnetogram: Generative Forecasting of Solar Evolution
Investigating the solar magnetic field is crucial to understand the physical processes in the solar interior as well as their effects on the interplanetary environment. We introduce a novel method to predict the evolutio…
DenoisingImage-to-Image TranslationAnalysis and Predictive Modeling of Solar Coronal Holes Using Computer Vision and ARIMA-LSTM Networks
In the era of space exploration, coronal holes on the sun play a significant role due to their impact on satellites and aircraft through their open magnetic fields and increased solar wind emissions. This study employs c…
Time SeriesTime Series PredictionSurya: Foundation Model for Heliophysics
Heliophysics is central to understanding and forecasting space weather events and solar activity. Despite decades of high-resolution observations from the Solar Dynamics Observatory (SDO), most models remain task-specifi…
New approach for solar tracking systems based on computer vision, low cost hardware and deep learning
In this work, a new approach for Sun tracking systems is presented. Due to the current system limitations regarding costs and operational problems, a new approach based on low cost, computer vision open hardware and deep…
Shadow Detection