Object classification with Convolutional Neural Networks: from KiDS to Euclid

• DOI: 10.48550/arxiv.2403.01613
• Publication Date: 2024-03-03
• Authors: G. A. Verdoes Kleijn; Cristian A. Marocico; Yasmin Mzayek; M. Pöntinen; Mikael Granvik; O. R. Williams; J. T. A. de Jong; T. Saifollahi; Laishuan Wang; B. Margalef-Bentabol; Antonio La Marca; Bharath Chowdhary...; L. V. E. Koopmans; E. A. Valentijn

Large-scale imaging surveys have grown about 1000 times faster than the number of astronomers in last 3 decades. Using Artificial Intelligence instead astronomer's brains for interpretative tasks allows to keep up with data. We give a progress report on using Convolutional Neural Networks (CNNs) classify three classes rare objects (galaxy mergers, strong gravitational lenses and asteroids) Kilo-Degree Survey (KiDS) Euclid Survey.