文章基本信息

标题：A large-scale solar dynamics observatory image dataset for computer vision applications
本地全文：下载
作者：Ahmet Kucuk ; Juan M. Banda ; Rafal A. Angryk 等
期刊名称：Scientific Data
电子版ISSN：2052-4463
出版年度：2017
卷号：4
DOI：10.1038/sdata.2017.96
语种：English
出版社：Nature Publishing Group
摘要：The National Aeronautics Space Agency (NASA) Solar Dynamics Observatory (SDO) mission has given us unprecedented insight into the Sun鈥檚 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鈥檚 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.