14 citations · 31 across the 3 of their papers we have counts for
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Deep learning-based radiointerferometric imaging with GAN-aided training
F. Geyer, K. Schmidt, J. Kummer +7
Radio interferometry invariably suffers from an incomplete coverage of the spatial Fourier space, which leads to imaging artifacts. The current state-of-the-art technique is to cre…
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…