Titel

Merkliste
1 Ergebnisse

Radio Galaxy Zoo: using semi-supervised learning to leverag..:

Slijepcevic, Inigo V ; Scaife, Anna M M ; Walmsley, Mike...
Slijepcevic , I V , Scaife , A M M , Walmsley , M , Bowles , M , Wong , O I , Shabala , S S & Tang , H 2022 , ' Radio Galaxy Zoo: using semi-supervised learning to leverage large unlabelled data sets for radio galaxy classification under data set shift ' , Monthly Notices of the Royal Astronomical Society , vol. 514 , no. 2 , pp. 2599-2613 . https://doi.org/10.1093/mnras/stac1135. , 2022

Link: https://research.manchester.ac.uk/en/publications/ad05..

RT Journal
T1 <Title>Radio Galaxy Zoo: using semi-supervised learning to leverage large unlabelled data sets for radio galaxy classification under data set shift</Title>

UL https://suche.suub.uni-bremen.de/peid=base-ftumanchesterpub:oai:pure.atira.dk:publications_ad0586e4-c47a-4ddf-a13c-5c8d01335eb8&Exemplar=1&LAN=DE
				
A1 Slijepcevic, Inigo V
A1 Scaife, Anna M M
A1 Walmsley, Mike
A1 Bowles, Micah
A1 Wong, O Ivy
A1 Shabala, Stanislav S
A1 Tang, Hongming
YR 2022
K1 Methods: data analysis
K1 Methods: statistical
K1 Radio continuum: galaxies
JF Slijepcevic , I V , Scaife , A M M , Walmsley , M , Bowles , M , Wong , O I , Shabala , S S & Tang , H 2022 , ' Radio Galaxy Zoo: using semi-supervised learning to leverage large unlabelled data sets for radio galaxy classification under data set shift ' , Monthly Notices of the Royal Astronomical Society , vol. 514 , no. 2 , pp. 2599-2613 . https://doi.org/10.1093/mnras/stac1135
LK http://dx.doi.org/https://research.manchester.ac.uk/en/publications/ad0586e4-c47a-4ddf-a13c-5c8d01335eb8
DO https://research.manchester.ac.uk/en/publications/ad0586e4-c47a-4ddf-a13c-5c8d01335eb8
SF ELIB - SuUB Bremen

Export

RefWorks (nur Desktop-Version!)
Flow (Zuerst in Flow einloggen, dann importieren)