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
A Personalized and Differentially Private Federated Learnin..:
Zhang, Zhen
;
Zhang, Weishan
;
Bao, Zhicheng
...
IEEE Journal of Radio Frequency Identification. 8 (2024) - p. 468-475 , 2024
Link:
https://doi.org/10.1109/jrfid.2024.3390142
RT Journal T1 <Title>A Personalized and Differentially Private Federated Learning for Anomaly Detection of Industrial Equipment</Title> UL https://suche.suub.uni-bremen.de/peid=cr-10.1109_jrfid.2024.3390142&Exemplar=1&LAN=DE A1 Zhang, Zhen A1 Zhang, Weishan A1 Bao, Zhicheng A1 Miao, Yifan A1 Liu, Yuru A1 Zhao, Yikang A1 Zhang, Rui A1 Zhu, Wenyin PB Institute of Electrical and Electronics Engineers (IEEE) YR 2024 SN 2469-7281 SN 2469-729X JF IEEE Journal of Radio Frequency Identification VO 8 SP 468 OP 475 LK http://dx.doi.org/https://doi.org/10.1109/jrfid.2024.3390142 DO https://doi.org/10.1109/jrfid.2024.3390142 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
