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
Received Signal Strength Prediction Using Generative Advers..:
, In:
2023 Photonics & Electromagnetics Research Symposium (PIERS)
,
Wu, Haochang
;
Qin, Hao
;
Ma, Siteng
.. - p. 351-354 , 2023
Link:
https://doi.org/10.1109/PIERS59004.2023.10221373
RT T1
2023 Photonics & Electromagnetics Research Symposium (PIERS)
: T1
Received Signal Strength Prediction Using Generative Adversarial Networks for Indoor Localization
UL https://suche.suub.uni-bremen.de/peid=ieee-10221373&Exemplar=1&LAN=DE A1 Wu, Haochang A1 Qin, Hao A1 Ma, Siteng A1 Lang, Hans-Dieter A1 Zhang, Xingqi YR 2023 SN 2831-5804 K1 Location awareness K1 Costs K1 Smart buildings K1 Databases K1 Fingerprint recognition K1 Wireless access points K1 Generative adversarial networks SP 351 OP 354 LK http://dx.doi.org/https://doi.org/10.1109/PIERS59004.2023.10221373 DO https://doi.org/10.1109/PIERS59004.2023.10221373 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)