Dr Fiorenzo Stoppa: Publications

AutoSourceID-Light

Astronomy & Astrophysics EDP Sciences 662 (2022) A109-A109

Authors:

F Stoppa, P Vreeswijk, S Bloemen, S Bhattacharyya, S Caron, G Jóhannesson, R Ruiz de Austri, C van den Oetelaar, G Zaharijas, PJ Groot, E Cator, G Nelemans

Abstract:

Aims.With the ever-increasing survey speed of optical wide-field telescopes and the importance of discovering transients when they are still young, rapid and reliable source localization is paramount. We present AutoSourceID-Light (ASID-L), an innovative framework that uses computer vision techniques that can naturally deal with large amounts of data and rapidly localize sources in optical images.Methods.We show that the ASID-L algorithm based on U-shaped networks and enhanced with a Laplacian of Gaussian filter provides outstanding performance in the localization of sources. A U-Net network discerns the sources in the images from many different artifacts and passes the result to a Laplacian of Gaussian filter that then estimates the exact location.Results.Using ASID-L on the optical images of the MeerLICHT telescope demonstrates the great speed and localization power of the method. We compare the results with SExtractor and show that our method outperforms this more widely used method. ASID-L rapidly detects more sources not only in low- and mid-density fields, but particularly in areas with more than 150 sources per square arcminute. The training set and code used in this paper are publicly available.

MeerCRAB: MeerLICHT classification of real and bogus transients using deep learning

Experimental Astronomy Springer Science and Business Media LLC 51:2 (2021) 319-344

Authors:

Zafiirah Hosenie, Steven Bloemen, Paul Groot, Robert Lyon, Bart Scheers, Benjamin Stappers, Fiorenzo Stoppa, Paul Vreeswijk, Simon De Wet, Marc Klein Wolt, Elmar Körding, Vanessa McBride, Rudolf Le Poole, Kerry Paterson, Daniëlle LA Pieterse, Patrick Woudt

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