Multi-frequency point source detection with fully convolutional networks: Performance in realistic microwave sky simulations

• Published in: Astronomy and astrophysics (Berlin) Vol. 658; p. A110
• Main Authors: Casas, J. M., González-Nuevo, J., Bonavera, L., Herranz, D., Suarez Gomez, S. L., Cueli, M. M., Crespo, D., Santos, J. D., Sánchez, M. L., Sánchez-Lasheras, F., de Cos, F. J.
• Format: Journal Article
• Language: English
• Published: Heidelberg EDP Sciences 01.02.2022
• Subjects: Artificial intelligence; Artificial neural networks; Completeness; Contaminants; Cosmic microwave background; Filtration; Flux density; Neural networks; Point sources; Simulation; Spectra; Thermal emission

Context. Point source (PS) detection is an important issue for future cosmic microwave background (CMB) experiments since they are one of the main contaminants to the recovery of CMB signal on small scales. Improving its multi-frequency detection would allow us to take into account valuable informat...