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
Resource Efficient Federated Learning for Deep Anomaly Dete..:
, In:
2023 24th International Conference on Digital Signal Processing (DSP)
,
Gkillas, Alexandros
;
Lalos, Aris
- p. 1-5 , 2023
Link:
https://doi.org/10.1109/DSP58604.2023.10167873
RT T1
2023 24th International Conference on Digital Signal Processing (DSP)
: T1
Resource Efficient Federated Learning for Deep Anomaly Detection in Industrial IoT applications
UL https://suche.suub.uni-bremen.de/peid=ieee-10167873&Exemplar=1&LAN=DE A1 Gkillas, Alexandros A1 Lalos, Aris YR 2023 SN 2165-3577 K1 Performance evaluation K1 Federated learning K1 Image edge detection K1 Computational modeling K1 Time series analysis K1 Digital signal processing K1 Data models K1 anomaly detection K1 compression K1 federated learning K1 multidimensional time series SP 1 OP 5 LK http://dx.doi.org/https://doi.org/10.1109/DSP58604.2023.10167873 DO https://doi.org/10.1109/DSP58604.2023.10167873 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)