Solar active regions are where sunspots are located and photospheric magnetic fluxes are concentrated, therefore being the sources of energetic eruptions in the solar atmosphere. The detection and statistics of solar active regions have been forefront topics in solar physics. In this study, we developed a solar active region detector (SARD) based on the advanced object detection model YOLOv8. First, we applied image processing techniques including thresholding and morphological operations to 6975 line-of-sight magnetograms from 2010 to 2019 at a cadence of 12~h, obtained by the Helioseismic and Magnetic Imager onboard the Solar Dynamic Observatory. With manual refinement, we labeled 26531 active regions in the dataset for further training and test with the detection model. Without any overlap between the training and test sets, the superior performance of SARD is demonstrated by an average precision rate as high as 94\%. We then performed a statistical analysis on the area and magnetic flux of the detected active regions, both of which yield log-normal distributions. This result sheds light on the underlying complexity and multi-scale nature of solar active regions.
@article{arxiv.2507.21866,
title = {SARD: A YOLOv8-Based System for Solar Active Region Detection with SDO/HMI Magnetograms},
author = {Jinhui Pan and Jiajia Liu and Shaofeng Fang and Rui Liu},
journal= {arXiv preprint arXiv:2507.21866},
year = {2025}
}