DeepShadows: Finding low-surface-brightness galaxies in survey images
Abstract
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.
- Publication:
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Astrophysics Source Code Library
- Pub Date:
- November 2020
- Bibcode:
- 2020ascl.soft11026T
- Keywords:
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- Software