Galaxies The information that can be extracted from an image of a galaxy is fundamentally limited by the resolution and noise in the data. Schawinski et al. have applied a machine learning method to galaxy images, which is trained by comparing artificially degraded images with the originals. The algorithm is then used to recover features from previously unseen degraded images, which it performs more successfully than traditional deconvolution techniques. The method requires assuming that the target galaxies look similar to those in the training set, and individual details can be lost or misidentified, but it should be useful for studying statistical properties of galaxies in large surveys. Mon. Not. R. Astron. Soc. 467 , L110 (2017).

中文翻译：

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从嘈杂的数据中恢复星系图像

星系 可以从星系图像中提取的信息从根本上受到数据分辨率和噪声的限制。沙温斯基等人。已经将机器学习方法应用于星系图像，通过将人工退化的图像与原始图像进行比较来训练。然后使用该算法从以前看不见的退化图像中恢复特征，它比传统的反卷积技术执行得更成功。该方法需要假设目标星系看起来与训练集中的星系相似，个别细节可能会丢失或被错误识别，但它对于研究大型调查中星系的统计特性应该很有用。星期一 不是。R. 阿斯特朗。社会。467, L110 (2017)。