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[ascl:1805.029] DeepMoon: Convolutional neural network trainer to identify moon craters

DeepMoon trains a convolutional neural net using data derived from a global digital elevation map (DEM) and catalog of craters to recognize craters on the Moon. The TensorFlow-based pipeline code is divided into three parts. The first generates a set images of the Moon randomly cropped from the DEM, with corresponding crater positions and radii. The second trains a convnet using this data, and the third validates the convnet's predictions.

Code site:
https://github.com/silburt/DeepMoon
Appears in:
http://adsabs.harvard.edu/abs/2018arXiv180302192S
Bibcode:
2018ascl.soft05029S

Views: 417

ascl:1805.029
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