8 citations · 10 across the 6 of their papers we have counts for
3 papers · 1 filter
UltraPINK -- New possibilities to explore Self-Organizing Kohonen Maps
Fenja Kollasch, Kai Polsterer
Unsupervised learning algorithms like self-organizing Kohonen maps are a promising approach to gain an overview among massive datasets. With UltraPINK, researchers can train, inspe…
Rotation and flipping invariant self-organizing maps with astronomical images: A cookbook and application to the VLA Sky Survey QuickLook images
A. N. Vantyghem, T. J. Galvin, B. Sebastian +12
Modern wide field radio surveys typically detect millions of objects. Techniques based on machine learning are proving to be useful for classifying large numbers of objects. The se…
PSF quality metrics in the problem of revealing Intermediate-Mass Black Holes using MICADO@ELT
Mariia Demianenko, Joerg-Uwe Pott, Kai Polsterer
Nowadays, astronomers perform point spread function (PSF) fitting for most types of observational data. Interpolation of the PSF is often an intermediate step in such algorithms. I…