Solar Image

Solar image analysis is crucial for understanding and predicting space weather, encompassing tasks like identifying solar active regions and coronal holes, and estimating thermospheric density. Current research heavily utilizes deep learning, employing architectures such as U-Nets, convolutional neural networks (CNNs), and transformers, often incorporating multi-spectral data and addressing challenges like cloud shadow removal and data compression for efficient transmission. These advancements improve the accuracy and timeliness of space weather forecasting, with implications for satellite operations, power grid stability, and overall risk mitigation.