Difference between revisions of "Galaxy morphology auto classification"
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#Deep learning for galaxy surface brightness profile fitting, MNRAS, Volume 475, Issue 1, March 2018 [https://academic.oup.com/mnras/article/475/1/894/4725057] | #Deep learning for galaxy surface brightness profile fitting, MNRAS, Volume 475, Issue 1, March 2018 [https://academic.oup.com/mnras/article/475/1/894/4725057] | ||
#The weirdest SDSS galaxies: results from an outlier detection algorithm, 2017,MNRAS,465,4530B, [https://ui.adsabs.harvard.edu/abs/2017MNRAS.465.4530B/abstract] | #The weirdest SDSS galaxies: results from an outlier detection algorithm, 2017,MNRAS,465,4530B, [https://ui.adsabs.harvard.edu/abs/2017MNRAS.465.4530B/abstract] | ||
#An automatic taxonomy of galaxy morphology using unsupervised machine learning, 2018, MNRAS, 473, 1108, [https://arxiv.org/abs/1709.05834] | |||
#Galaxy morphology classification with deep convolutional neural networks, 2019, Astrophysics and Space Science, Volume 364, Issue 4, article id. 55, [https://arxiv.org/abs/1807.10406] | #Galaxy morphology classification with deep convolutional neural networks, 2019, Astrophysics and Space Science, Volume 364, Issue 4, article id. 55, [https://arxiv.org/abs/1807.10406] | ||
#Machine and Deep Learning Applied to Galaxy Morphology -- A Comparative Study, 2020, Astronomy and Computing, Volume 30, article id. 100334, [https://arxiv.org/abs/1901.07047] | #Machine and Deep Learning Applied to Galaxy Morphology -- A Comparative Study, 2020, Astronomy and Computing, Volume 30, article id. 100334, [https://arxiv.org/abs/1901.07047] |
Revision as of 07:49, 9 March 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
- Pixel-based deep learning technic
- Special objects from auto-classification
Seminors
datasets
tools
- Morpheus [3]
- DeepGalaxy (Deep learning to classify the properties of galaxy mergers) [4]
- GalaxyMorphology [5]
references
- Deep learning for galaxy surface brightness profile fitting, MNRAS, Volume 475, Issue 1, March 2018 [6]
- The weirdest SDSS galaxies: results from an outlier detection algorithm, 2017,MNRAS,465,4530B, [7]
- An automatic taxonomy of galaxy morphology using unsupervised machine learning, 2018, MNRAS, 473, 1108, [8]
- Galaxy morphology classification with deep convolutional neural networks, 2019, Astrophysics and Space Science, Volume 364, Issue 4, article id. 55, [9]
- Machine and Deep Learning Applied to Galaxy Morphology -- A Comparative Study, 2020, Astronomy and Computing, Volume 30, article id. 100334, [10]
- Shadows in the Dark: Low-surface-brightness Galaxies Discovered in the Dark Energy Survey,2021,ApJS,252,18T,[11]
- Dwarfs from the Dark (Energy Survey): a machine learning approach to classify dwarf galaxies from multi-band image, arXiv:2102.12776,[12]
links
- THE COSMOSTATISTICS INITIATIVE [13]