Faculty Sponsor
Azim Ahmadzadeh
Final Abstract for URS Program
The observation and classification of solar filaments has a drastic impact on the ability to predict solar-magnetic weather phenomena that threatens to put both satellite infrastructure and astronauts at risk. Using the Hɑ filter provided by the Global Oscillations Network Group (GONG), a network of six telescopes around the world dedicated to 24/7 surveillance of the sun, we are able to get images that clearly and prominently display filament activity. With the vast amount of images the GONG takes, it is not possible to manually analyze every image. Using the U-Net model for computer vision, we were able to train an artificial intelligence (AI) model that can confidently segment out solar filaments of varying orientations, sizes, and clusters. In addition to the success of broad segmentation, we are able to get fine detail in the segmentation masks, which is crucial for classifying the chirality of filaments for more precise storm prediction.
Presentation Type
Visual Presentation
Document Type
Article