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(1 - 5 of 5)
Finding AGN remnant candidates based on radio morphology with machine learning
Mostert, R.I.J.; Morganti, R.; Brienza, M.; Duncan, K.J.; Oei, M.S.S.L.; Röttgering, H.J.A.; ... ; Jurlin, N. 2023
Finding AGN remnant candidates based on radio morphology with machine learning
Article / Letter to editor
open access
A multi-band AGN-SFG classifier for extragalactic radio surveys using machine learning
Karsten, J.; Wang, L.; Margalef-Bentabol, B.; Best, P.N.; Kondapally, R.; La Marca, A.; ... ; Sabater, J. 2023
A multi-band AGN-SFG classifier for extragalactic radio surveys using machine learning
Article / Letter to editor
open access
Radio source-component association for the LOFAR Two-metre Sky Survey with region-based convolutional neural networks
Mostert, R.I.J.; Duncan, K.J.; Alegre, L.; Röttgering, H.J.A.; Williams, W.L.; Best, P.N.; ... ; Morganti, R. 2022
Radio source-component association for the LOFAR Two-metre Sky Survey with region-based convolutional neural networks
Article / Letter to editor
open access
The LOFAR Two-metre Sky Survey
Shimwell, T.W.; Hardcastle, M.J.; Tasse, C.; Best, P.N.; Röttgering, H.J.A.; Williams, W.L.; ... ; Zheng, J. 2022
The LOFAR Two-metre Sky Survey: V. Second data release
Article / Letter to editor
open access
Unveiling the rarest morphologies of the LOFAR two-metre sky survey radio source population with self-organised maps
Mostert, R.I.J.; Duncan, K.J.; Rottgering, H.J.A.; Polsterer, K.L.; Best, P.N.; Brienza, M.; ... ; Williams, W.L. 2021
Unveiling the rarest morphologies of the LOFAR two-metre sky survey radio source population with self-organised maps
Article / Letter to editor
open access