Mostrar el registro sencillo del ítem
Constraining the polarisation flux density and angle of point sources by training a convolutional neural network
| dc.contributor.author | Casas González, José Manuel | |
| dc.contributor.author | Bonavera, Laura | |
| dc.contributor.author | González-Nuevo González, Joaquín | |
| dc.contributor.author | Muñiz Cueli, Marcos | |
| dc.contributor.author | Crespo Iglesias, David | |
| dc.contributor.author | Goitia, E. | |
| dc.contributor.author | González Gutiérrez, Carlos | |
| dc.contributor.author | Santos Rodríguez, Jesús Daniel | |
| dc.contributor.author | Sánchez Rodríguez, María Luisa | |
| dc.contributor.author | Cos Juez, Francisco Javier de | |
| dc.date.accessioned | 2023-05-18T08:19:56Z | |
| dc.date.available | 2023-05-18T08:19:56Z | |
| dc.date.issued | 2023 | |
| dc.identifier.citation | Astronomy and Astrophysics, 670, (2023); doi:10.1051/0004-6361/202244424 | |
| dc.identifier.issn | 0004-6361 | |
| dc.identifier.uri | http://hdl.handle.net/10651/67863 | |
| dc.description.sponsorship | J.M.C., L.B., J.G.N., M.M.C. and D.C. acknowledge financial support from the PID2021-125630NB-I00 project funded by MCIN/AEI/10.13039/501100011033/FEDER, UE. J.M.C. also acknowledges financial support from the SV-PA-21-AYUD/2021/51301 project. M.M.C. also acknowledges to be granted by PAPI-21-PF-04 (Universidad de Oviedo). C.G.C., J.D.S., M.L.S. and F.J.D.C. acknowledge financial support from both PID2021- 127331NB-I00 and UE-18-SOLARNET-824135 projects | |
| dc.language.iso | eng | |
| dc.relation.ispartof | Astronomy and Astrophysics | |
| dc.rights | © The Authors 2023 | |
| dc.rights | CC Reconocimiento 4.0 Internacional | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.source | Scopus | |
| dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147849412&doi=10.1051%2f0004-6361%2f202244424&partnerID=40&md5=4209efccc700f7a6784ddcac69eaf694 | |
| dc.title | Constraining the polarisation flux density and angle of point sources by training a convolutional neural network | |
| dc.type | journal article | |
| dc.identifier.doi | 10.1051/0004-6361/202244424 | |
| dc.relation.projectID | PID2021-125630NB-I00 | |
| dc.relation.projectID | PAPI-21-PF-04 | |
| dc.relation.projectID | SV-PA-21-AYUD/2021/51301 | |
| dc.relation.projectID | PID2021-127331NB-I00 | |
| dc.relation.projectID | UE-18-SOLARNET-82413 | |
| dc.relation.publisherversion | http://dx.doi.org/10.1051/0004-6361/202244424 | |
| dc.rights.accessRights | open access | |
| dc.type.hasVersion | VoR |
Ficheros en el ítem
Este ítem aparece en la(s) siguiente(s) colección(ones)
-
Artículos [34682]
-
Física [1934]
-
Investigaciones y Documentos OpenAIRE [7614]
Publicaciones resultado de proyectos financiados con fondos públicos
Este ítem está sujeto a una licencia Creative Commons