Department of Computer Science, Georgia State University Atlanta 30302-3987, USA.
Sci Data. 2017 Jul 25;4:170096. doi: 10.1038/sdata.2017.96. eCollection 2017.
The National Aeronautics Space Agency (NASA) Solar Dynamics Observatory (SDO) mission has given us unprecedented insight into the Sun's activity. By capturing approximately 70,000 images a day, this mission has created one of the richest and biggest repositories of solar image data available to mankind. With such massive amounts of information, researchers have been able to produce great advances in detecting solar events. In this resource, we compile SDO solar data into a single repository in order to provide the computer vision community with a standardized and curated large-scale dataset of several hundred thousand solar events found on high resolution solar images. This publicly available resource, along with the generation source code, will accelerate computer vision research on NASA's solar image data by reducing the amount of time spent performing data acquisition and curation from the multiple sources we have compiled. By improving the quality of the data with thorough curation, we anticipate a wider adoption and interest from the computer vision to the solar physics community.
美国国家航空航天局（NASA）的太阳动力学观测站（SDO）任务让我们对太阳活动有了前所未有的深入了解。通过每天捕获大约 70000 张图像，该任务创建了人类可用的最丰富、最大的太阳图像数据集之一。有了如此大量的信息，研究人员能够在探测太阳事件方面取得重大进展。在这个资源中，我们将 SDO 太阳数据整合到一个单一的存储库中，以便为计算机视觉社区提供一个标准化和经过精心整理的、包含数十万在高分辨率太阳图像上发现的太阳事件的大规模数据集。这个公开可用的资源，以及生成的源代码，将通过减少从我们编译的多个源中执行数据采集和整理所花费的时间，来加速对 NASA 太阳图像数据的计算机视觉研究。通过彻底整理来提高数据质量，我们预计计算机视觉和太阳物理学社区会更广泛地采用和关注。
