“Galaxy morphology auto classification”的版本间差异
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无编辑摘要 |
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* DESI Legacy Imaging Surveys [https://www.legacysurvey.org/dr9/files/] |
* DESI Legacy Imaging Surveys [https://www.legacysurvey.org/dr9/files/] |
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* galaxy pair catalog [http://202.127.29.3/~shen/isopair/] |
* galaxy pair catalog [http://202.127.29.3/~shen/isopair/] |
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==Methods== |
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* Non-Negative Matrix Factorization |
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*Image Fourier Power Spectrum |
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*Auto-encoders (Rupesh) |
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*Watershed (Image Segmentation) |
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==tools== |
==tools== |
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==references== |
==references== |
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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] |
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#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] |
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#An automatic taxonomy of galaxy morphology using unsupervised machine learning, 2018, MNRAS, 473, 1108, [https://arxiv.org/abs/1709.05834] |
#An automatic taxonomy of galaxy morphology using unsupervised machine learning, 2018, MNRAS, 473, 1108, [https://arxiv.org/abs/1709.05834] |
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#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] |
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2021年5月20日 (四) 02:06的版本
- This page makes collections for galaxy morphology auto classification project of CSST image survey
projects
started
- merger identification
- Morphology of Alfalfa galaxies
- Unsupervised classification on images
- bar features
possibilities
- Classification in parameter space (e.g. parameters from Sextractor)
- Pixel-based deep learning technic
- Special objects from auto-classification
Meetings
- Mar. 4/2021
- Minutes of exercises on Galaxy Classification Meeting [1]
datasets
- galaxy zoo data [2]
- Galaxy Zoo DECaLS[3]
Methods
- Non-Negative Matrix Factorization
- Image Fourier Power Spectrum
- Auto-encoders (Rupesh)
- Watershed (Image Segmentation)
tools
- Morpheus [6]
- DeepGalaxy (Deep learning to classify the properties of galaxy mergers) [7]
- GalaxyMorphology [8]
- lenstronomy [9]
- Unsupervised Image Classification [10]
references
- Deep learning for galaxy surface brightness profile fitting, MNRAS, Volume 475, Issue 1, March 2018 [11]
- The weirdest SDSS galaxies: results from an outlier detection algorithm, 2017, MNRAS,465,4530B, [12]
- An automatic taxonomy of galaxy morphology using unsupervised machine learning, 2018, MNRAS, 473, 1108, [13]
- Galaxy morphology classification with deep convolutional neural networks, 2019, Astrophysics and Space Science, Volume 364, Issue 4, article id. 55, [14]
- Machine and Deep Learning Applied to Galaxy Morphology -- A Comparative Study, 2020, Astronomy and Computing, Volume 30, article id. 100334, [15]
- Shadows in the Dark: Low-surface-brightness Galaxies Discovered in the Dark Energy Survey,2021,ApJS,252,18T,[16]
- Dwarfs from the Dark (Energy Survey): a machine learning approach to classify dwarf galaxies from multi-band image, arXiv:2102.12776,[17]
links
- THE COSMOSTATISTICS INITIATIVE [18]