第四十六章 天文学家的助手

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教学资料


扩展阅读

  • AI100问:机器学习如何帮助天文学家检测望远镜问题?[2]
  • 最强大射电望远镜亮相由66座天线构成 [3]
  • 新华社:中国天眼”——500米口径球面射电望远镜(FAST) [4]
  • 大国重器“中国天眼” [5]
  • 这只“中国天眼”:看透百亿光年 洞悉星辰大海[6]
  • 维基百科:中国天眼 [7]
  • At 13 Billion Light-Years Away, Galaxy Is Farthest To Be Measured From Earth [8]


视频展示

  • CCTV-9 纪录片《天眼》 [9]
  • 哈伯望远镜传回的照片 [10]
  • 纪录片《哈勃望远镜》 [11]
  • Classifying Galaxies with AI [12]
  • Big data in astronomy [13]
  • AI and space industry [14]


演示链接

开发者资源

  • AstroCV: an oper source toolbox for astronomy [15]
  • Source code for checking astronomy data (Mesarcik et al.)[16]
  • Source code for DFCN-based RFI detection (Kerrigan et al.) [17]

高级读者

  • Baron D. Machine learning in astronomy: A practical overview[J]. arXiv preprint arXiv:1904.07248, 2019. [18]
  • Henry W. Leung1 and Jo Bovy, Deep learning of multi-element abundances from high-resolution spectroscopic data, MNRAS, 2018. [19]
  • Mesarcik et al, Deep learning assisted data inspection for radio astronomy, MNRAS, 2020. [20]
  • Kerrigan J, Plante P L, Kohn S, et al. Optimizing sparse RFI prediction using deep learning[J]. Monthly Notices of the Royal Astronomical Society, 2019, 488(2): 2605-2615. [21]
  • González R E, Munoz R P, Hernández C A. Galaxy detection and identification using deep learning and data augmentation[J]. Astronomy and computing, 2018, 25: 103-109. [22]