Speaker
Andrei Kazantsev
(Max-Planck-Institut für Radioastronomie)
Description
As part of the PUNCH4DFDI project at the Max Planck Institute for Radio Astronomy, a deep learning-based pipeline is being developed for the automatic classification of astronomical radio signals in real-time. A prototype utilizing deep learning techniques has been created to classify emissions from the pulsar in the Crab Nebula. The next step involves expanding the model's capabilities to successfully detect pulses from different pulsars, with other dispersion measures and in other frequency ranges. During the discussion group, a live discussion is planned to explore possible approaches for implementing this scaling.
