Difference between revisions of "Deep learning on galaxy images: training dataset"
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* A sample of CGS galaxies{https://arxiv.org/abs/1111.4605] manually move to high redshifts and observed in other surveys(PS1, SDSS stripe82, CANDELS_AEGIS , Hubble Frontier Fields | * A sample of CGS galaxies{https://arxiv.org/abs/1111.4605] manually move to high redshifts and observed in other surveys(PS1, SDSS stripe82, CANDELS_AEGIS , Hubble Frontier Fields | ||
:*The Carnegie-Irvine Galaxy Survey (CGS) is a long-term program to investigate the photometric and spectroscopic properties of a statistically complete sample of 605 bright (BT < 12.9mag), southern (δ < 0°) galaxies using the facilities at Las Campanas Observatory. | :*The Carnegie-Irvine Galaxy Survey (CGS) is a long-term program to investigate the photometric and spectroscopic properties of a statistically complete sample of 605 bright (BT < 12.9mag), southern (δ < 0°) galaxies using the facilities at Las Campanas Observatory. | ||
:*contact Shiyin Shen for more infomation | |||
Revision as of 08:40, 11 November 2021
This page is used to collect the training dataset for deep learning applications on galaxy images.
If you want to contribute, please contact Shiyin Shen (ssy@shao.ac.cn)
local galaxy sample
- galaxy zoo data [1]
high z galaxy sample
- COSMOS F814W galaxy postages
- CANDELS 5 fields galaxy postages (H<24.5)
Mock galaxies
- generate using GalSim (with CSST-like survey parameters)
- tel_diam=200mm, exptime=150s, lam=5500A, sky_mag=23, psf_sigma=0.2, gain=1, readnoise=5, pixel_scale=0.074
- generate using GalSim-Hub[4]
- A sample of CGS galaxies{https://arxiv.org/abs/1111.4605] manually move to high redshifts and observed in other surveys(PS1, SDSS stripe82, CANDELS_AEGIS , Hubble Frontier Fields
- The Carnegie-Irvine Galaxy Survey (CGS) is a long-term program to investigate the photometric and spectroscopic properties of a statistically complete sample of 605 bright (BT < 12.9mag), southern (δ < 0°) galaxies using the facilities at Las Campanas Observatory.
- contact Shiyin Shen for more infomation