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[ascl:2011.026] DeepShadows: Finding low-surface-brightness galaxies in survey images

DeepShadows uses a convolutional neural networks (CNNs) to separate low-surface-brightness galaxies (LSBGs) from artifacts (such as Galactic cirrus and star-forming regions) in survey images. The model is trained and tested on labeled LSBGs and artifacts from the Dark Energy Survey and demonstrates that CNNs offer a promising path in the quest to study the low-surface-brightness universe.

Code site:
https://github.com/dtanoglidis/DeepShadows
Described in:
https://ui.adsabs.harvard.edu/abs/2020arXiv201112437T
Bibcode:
2020ascl.soft11026T

Views: 931

ascl:2011.026
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