65 citations · 85 across the 4 of their papers we have counts for
4 papers
Classification of Radio Sources Through Self-Supervised Learning
Nicolas Baron Perez, Marcus Brüggen, Gregor Kasieczka +1
The morphology of radio galaxies is indicative of their interaction with their surroundings, among other effects. Since modern radio surveys contain a large number of radio sources…
Morphological Classification of Radio Galaxies with wGAN-supported Augmentation
Lennart Rustige, Janis Kummer, Florian Griese +7
Machine learning techniques that perform morphological classification of astronomical sources often suffer from a scarcity of labelled training data. Here, we focus on the case of…
Radio Galaxy Classification with wGAN-Supported Augmentation
Janis Kummer, Lennart Rustige, Florian Griese +6
Novel techniques are indispensable to process the flood of data from the new generation of radio telescopes. In particular, the classification of astronomical sources in images is…
Morphological classification of radio galaxies: Capsule Networks versus Convolutional Neural Networks
V. Lukic, M. Brüggen, B. Mingo +3
Next-generation radio surveys will yield an unprecedented amount of data, warranting analysis by use of machine learning techniques. Convolutional neural networks are the deep lear…