Radio Galaxy Zoo Talk

And one more older blogpost: Radio Galaxy Zoo’s ClaRAN

  • JeanTate by JeanTate

    On the 31 October 2018, Radio Galaxy Zoo published its first end-to-end machine learning system for “Classifying Radio sources Automatically using Neural networks” (ClaRAN). This paper is led by ClaRAN’s developer, Chen Wu, a data scientist at the International Centre for Radio Astronomy Research at the University of Western Australia (ICRAR/UWA), who repurposed the FAST-rCNN algorithm (used by Microsoft and Facebook) to classify radio galaxies. ClaRAN was trained on radio galaxies classified by Radio Galaxy Zoo and so recognises some of the most common radio morphologies that have been classified.

    Radio Galaxy Zoo’s ClaRAN

    Also posted in RGZ Talk Journal Club, here.

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