Active Region

Solar active regions (ARs), intense areas of magnetic activity on the Sun, are the source of significant space weather events like solar flares and coronal mass ejections. Current research focuses on improving the prediction of AR emergence and flare occurrence using machine learning techniques, particularly deep learning architectures such as convolutional neural networks (CNNs) and long short-term memory networks (LSTMs), often applied to multi-spectral and time-series data from solar observatories. These advancements aim to enhance space weather forecasting accuracy, providing crucial early warnings for potential disruptions to Earth's technological infrastructure and improving our understanding of solar dynamics.

Papers

October 23, 2024

Deep Learning for Active Region Classification: A Systematic Study from Convolutional Neural Networks to Vision Transformers
Edoardo Legnaro, Sabrina Guastavino, Michele Piana, Anna Maria Massone
Deep Learning Convolutional Neural Network Vision Transformer Image Classification Systematic Study Active Region

September 25, 2024

Solar Active Regions Emergence Prediction Using Long Short-Term Memory Networks
Spiridon Kasapis, Irina N. Kitiashvili, Alexander G. Kosovichev, John T. Stefan
Long Short Term Memory Magnetic Field Solar Dynamic Observatory Active Region

July 19, 2024

MLMT-CNN for Object Detection and Segmentation in Multi-layer and Multi-spectral Images
Majedaldein Almahasneh, Adeline Paiement, Xianghua Xie, Jean Aboudarham
Segmentation Based Approach Multi Layer Multi Spectral Solar Image Active Region Coronal Hole GMM CNN

June 16, 2024

Advancing Solar Flare Prediction using Deep Learning with Active Region Patches
Chetraj Pandey, Temitope Adeyeha, Jinsu Hong, Rafal A. Angryk, Berkay Aydin
Deep Learning Solar Flare Protoplanetary Disk Active Region Flare Forecasting

March 27, 2024

Super-Resolution of SOHO/MDI Magnetograms of Solar Active Regions Using SDO/HMI Data and an Attention-Aided Convolutional Neural Network
Chunhui Xu, Jason T. L. Wang, Haimin Wang, Haodi Jiang, Qin Li, Yasser Abduallah, Yan Xu
Super Resolution Image Super Resolution Solar Dynamic Observatory Active Region

February 14, 2024

Predicting the Emergence of Solar Active Regions Using Machine Learning
Spiridon Kasapis, Irina N. Kitiashvili, Alexander G. Kosovichev, John T. Stefan, Bhairavi Apte
Machine Learning Path Breaking Emergence Magnetic Field Solar Dynamic Observatory Active Region

February 5, 2024

Active Region-based Flare Forecasting with Sliding Window Multivariate Time Series Forest Classifiers
Anli Ji, Berkay Aydin
Random Forest Generating User Activity Solar Flare Active Region Flare Forecasting Forest Classifier

May 16, 2023

Solar Active Region Magnetogram Image Dataset for Studies of Space Weather
Laura E. Boucheron, Ty Vincent, Jeremy A. Grajeda, Ellery Wuest
Study Feature Solar Flare Space Weather Active Region Solar Flare Prediction

November 4, 2022

A Deep Learning Approach to Generating Photospheric Vector Magnetograms of Solar Active Regions for SOHO/MDI Using SDO/HMI and BBSO Data
Haodi Jiang, Qin Li, Zhihang Hu, Nian Liu, Yasser Abduallah, Ju Jing, Genwei Zhang, Yan Xu, Wynne Hsu, Jason T. L. Wang, Haimin Wang
Deep Learning Approach Magnetic Field Solar Dynamic Observatory Active Region

April 7, 2022

Predicting Solar Flares Using CNN and LSTM on Two Solar Cycles of Active Region Data
Zeyu Sun, Monica G. Bobra, Xiantong Wang, Yu Wang, Hu Sun, Tamas Gombosi, Yang Chen, Alfred Hero
LSTM Network CNN Network Flare Prediction Active Region Solar Flare Prediction

Active Region

Papers

Deep Learning for Active Region Classification: A Systematic Study from Convolutional Neural Networks to Vision Transformers

Solar Active Regions Emergence Prediction Using Long Short-Term Memory Networks

MLMT-CNN for Object Detection and Segmentation in Multi-layer and Multi-spectral Images

Advancing Solar Flare Prediction using Deep Learning with Active Region Patches

Super-Resolution of SOHO/MDI Magnetograms of Solar Active Regions Using SDO/HMI Data and an Attention-Aided Convolutional Neural Network

Predicting the Emergence of Solar Active Regions Using Machine Learning

Active Region-based Flare Forecasting with Sliding Window Multivariate Time Series Forest Classifiers

Solar Active Region Magnetogram Image Dataset for Studies of Space Weather

A Deep Learning Approach to Generating Photospheric Vector Magnetograms of Solar Active Regions for SOHO/MDI Using SDO/HMI and BBSO Data

Predicting Solar Flares Using CNN and LSTM on Two Solar Cycles of Active Region Data