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
Deep Learning Techniques For Improving NearField Synthetic ..:
, In:
2024 IEEE 13th International Conference on Communication Systems and Network Technologies (CSNT)
,
Deepak, Shashikant
;
Kharbas, Vikash Kumar
;
R, Murugan
- p. 624-630 , 2024
Link:
https://doi.org/10.1109/CSNT60213.2024.10545795
RT T1 <cTitle>2024 IEEE 13th International Conference on Communication Systems and Network Technologies (CSNT)</cTitle>: T1 <Title>Deep Learning Techniques For Improving NearField Synthetic Aperture Radar Imaging</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10545795&Exemplar=1&LAN=DE A1 Deepak, Shashikant A1 Kharbas, Vikash Kumar A1 R, Murugan YR 2024 SN 2473-5655 K1 Deep learning K1 PSNR K1 Disasters K1 Object detection K1 Radar polarimetry K1 Calibration K1 Convolutional neural networks K1 Artificial intelligence K1 Environmental assessment K1 Image quality K1 Interpretability K1 Nearfield SAR K1 Peak Signal-to-Noise Ratio K1 Remote sensing K1 Synthetic Aperture Radar SP 624 OP 630 LK http://dx.doi.org/https://doi.org/10.1109/CSNT60213.2024.10545795 DO https://doi.org/10.1109/CSNT60213.2024.10545795 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
