Difference between revisions of "Galaxy morphology auto classification"
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==references== | ==references== | ||
#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] | ||
#Shadows in the Dark: Low-surface-brightness Galaxies Discovered in the Dark Energy Survey,2021,ApJS,252,18T,[https://ui.adsabs.harvard.edu/abs/2021ApJS..252...18T/abstract] | |||
==links== | ==links== | ||
*THE COSMOSTATISTICS INITIATIVE [https://cosmostatistics-initiative.org/] | *THE COSMOSTATISTICS INITIATIVE [https://cosmostatistics-initiative.org/] | ||
Revision as of 05:17, 4 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
datasets
tools
- Morpheus [3]
references
- Deep learning for galaxy surface brightness profile fitting, MNRAS, Volume 475, Issue 1, March 2018 [4]
- The weirdest SDSS galaxies: results from an outlier detection algorithm, 2017,MNRAS,465,4530B, [5]
- Shadows in the Dark: Low-surface-brightness Galaxies Discovered in the Dark Energy Survey,2021,ApJS,252,18T,[6]
links
- THE COSMOSTATISTICS INITIATIVE [7]