Radio galaxy zoo: Unsupervised clustering of convolutionally auto-encoded radio-astronomical images
This paper demonstrates a novel and efficient unsupervised clustering method with the combination of a self-organizing map (SOM) and a convolutional autoencoder. The rapidly increasing volume of radio-astronomical data has increased demand for machine-learning methods as solutions to classification...
| Main Authors: | , , , , , , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
IOP Publishing
2019
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