I agree that this site is using cookies. You can find further informations
here
.
X
Login
Merkliste (
0
)
Home
About us
Home About us
Our history
Profile
Press & public relations
Friends
The library in figures
Exhibitions
Projects
Training, internships, careers
Films
Services & Information
Home Services & Information
Lending and interlibrary loans
Returns and renewals
Training and library tours
My Account
Library cards
New to the library?
Download Information
Opening hours
Learning spaces
PC, WLAN, copy, scan and print
Catalogs and collections
Home Catalogs and Collections
Rare books and manuscripts
Digital collections
Subject Areas
Our sites
Home Our sites
Central Library
Law Library (Juridicum)
BB Business and Economics (BB11)
BB Physics and Electrical Engineering
TB Engineering and Social Sciences
TB Economics and Nautical Sciences
TB Music
TB Art & Design
TB Bremerhaven
Contact the library
Home Contact the library
Staff Directory
Open access & publishing
Home Open access & publishing
Reference management: Citavi & RefWorks
Publishing documents
Open Access in Bremen
zur Desktop-Version
Toggle navigation
Merkliste
1 Ergebnisse
1
TSSA: Two-Step Semi-Supervised Annotation for Radargrams on..:
, In:
IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium
,
Jebeli, Atefeh
;
Tama, Bayu Adhi
;
Janeja, Vandana P.
... - p. 56-59 , 2023
Link:
https://doi.org/10.1109/IGARSS52108.2023.10282880
RT T1
IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium
: T1
TSSA: Two-Step Semi-Supervised Annotation for Radargrams on the Greenland Ice Sheet
UL https://suche.suub.uni-bremen.de/peid=ieee-10282880&Exemplar=1&LAN=DE A1 Jebeli, Atefeh A1 Tama, Bayu Adhi A1 Janeja, Vandana P. A1 Holschuh, Nicholas A1 Jensen, Claire A1 Morlighem, Mathieu A1 MacGregor, Joseph A. A1 Fahnestock, Mark A. YR 2023 SN 2153-7003 K1 Training K1 Deep learning K1 Annotations K1 Computational modeling K1 Transfer learning K1 Data augmentation K1 Transformers K1 ice sheet K1 ice penetrating radar K1 supervised learning K1 unsupervised learning K1 deep neural network SP 56 OP 59 LK http://dx.doi.org/https://doi.org/10.1109/IGARSS52108.2023.10282880 DO https://doi.org/10.1109/IGARSS52108.2023.10282880 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)