Difference between revisions of "Galaxy morphology auto classification"

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* [[merger identification]]
* [[merger identification]]


==Seminors==
==Meetings==
* [[1st_seminor_morphology | Mar. 4/2021  ]]
* [[1st_seminor_morphology | Mar. 4/2021  ]]
* Minutes of exercises on Galaxy Classification Meeting [http://cluster.shao.ac.cn/wiki/index.php?title=Galaxy_morphology_auto_classification&action=edit&section=6]


==datasets==
==datasets==

Revision as of 08:52, 22 April 2021

  • This page makes collections for galaxy morphology auto classification project of CSST image survey

projects

  • Classification in parameter space (e.g. parameters from Sextractor)
  • Classification on images, CNN like technic

Meetings

datasets

  • galaxy zoo data [2]
  • DESI Legacy Imaging Surveys [3]

tools

  • Morpheus [4]
  • DeepGalaxy (Deep learning to classify the properties of galaxy mergers) [5]
  • GalaxyMorphology [6]
  • lenstronomy [7]

references

  1. Deep learning for galaxy surface brightness profile fitting, MNRAS, Volume 475, Issue 1, March 2018 [8]
  2. The weirdest SDSS galaxies: results from an outlier detection algorithm, 2017,MNRAS,465,4530B, [9]
  3. An automatic taxonomy of galaxy morphology using unsupervised machine learning, 2018, MNRAS, 473, 1108, [10]
  4. Galaxy morphology classification with deep convolutional neural networks, 2019, Astrophysics and Space Science, Volume 364, Issue 4, article id. 55, [11]
  5. Machine and Deep Learning Applied to Galaxy Morphology -- A Comparative Study, 2020, Astronomy and Computing, Volume 30, article id. 100334, [12]
  6. Shadows in the Dark: Low-surface-brightness Galaxies Discovered in the Dark Energy Survey,2021,ApJS,252,18T,[13]
  7. Dwarfs from the Dark (Energy Survey): a machine learning approach to classify dwarf galaxies from multi-band image, arXiv:2102.12776,[14]

links

  • THE COSMOSTATISTICS INITIATIVE [15]