Integrating human and machine intelligence in galaxy morphology classification tasks
Quantifying galaxy morphology is a challenging yet scientifically rewarding task. As the scale of data continues to increase with upcoming surveys, traditional classification methods will struggle to handle the load. We present a solution through an integration of visual and automated classification...
| Main Authors: | , , , , , , , , , , |
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| Format: | Journal article |
| Published: |
Oxford University Press
2018
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