Integrating human and machine intelligence in galaxy morphology classification tasks
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 classifications, preserving the best features of both human and …