标题： 基于自动化机器学习的天文图像质量评估 显示英文标题

标题： Astronomical Images Quality Assessment with Automated Machine Learning

摘要： 电子辅助天文学包括使用与望远镜耦合的数码相机捕捉深空图像，以显示通过直接观测无法看到的天体视图。 这种做法会产生大量数据，在观测会话后可以使用专用的图像编辑软件来增强这些数据。 在这项研究中，我们展示了图像质量评估如何可用于自动评定天文图像，并且我们还利用自动化机器学习开发了一个专用模型。 显示英文摘要

摘要： Electronically Assisted Astronomy consists in capturing deep sky images with a digital camera coupled to a telescope to display views of celestial objects that would have been invisible through direct observation. This practice generates a large quantity of data, which may then be enhanced with dedicated image editing software after observation sessions. In this study, we show how Image Quality Assessment can be useful for automatically rating astronomical images, and we also develop a dedicated model by using Automated Machine Learning.