chengsoonong / crowdastro

Cross-identification of radio objects and host galaxies by applying machine learning on crowdsourced training labels.

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crowdastro

This project aims to develop a machine learned method for cross-identifying radio objects and their host galaxies, using crowdsourced labels from the Radio Galaxy Zoo.

PyPI Travis-CI Documentation Status DOI

For setup details, see the documentation on Read the Docs.

For a brief description of each notebook, see the documentation here.

The cross-identification dataset is available on Zenodo.

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Cross-identification of radio objects and host galaxies by applying machine learning on crowdsourced training labels.

License:MIT License


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Language:Python 77.6%Language:Jupyter Notebook 22.1%Language:Shell 0.3%