Speaker
David Cornu
(Observatoire de Paris | PSL)
Description
Astronomical facilities generate ever-increasing data volumes, rapidly approaching the exascale. In this talk, I will introduce YOLO-CIANNA, a deep-learning object detector for astronomical images, and present results over simulated 2D continuum images and HI emission cubes from the SKAO SDCs. I will then discuss how the method could be applied to data from the SKA precursor and how we could combine heterogeneous data from other types of surveys to build an instrumental-context-aware detector.
| Contribution length | Middle |
|---|
Primary author
David Cornu
(Observatoire de Paris | PSL)
