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
Explore Deep Feature Learning to Power Equipment Monitoring..:
, In:
Proceedings of the 6th International Conference on High Performance Compilation, Computing and Communications
,
Lu, Xiaoxiong
;
Zhang, Jie
;
Chen, Kaihua
... - p. 144-149 , 2022
Link:
https://dl.acm.org/doi/10.1145/3546000.3546022
RT T1
Proceedings of the 6th International Conference on High Performance Compilation, Computing and Communications
: T1
Explore Deep Feature Learning to Power Equipment Monitoring and Defect Detection
UL https://suche.suub.uni-bremen.de/peid=acm-3546022&Exemplar=1&LAN=DE A1 Lu, Xiaoxiong A1 Zhang, Jie A1 Chen, Kaihua A1 Wu, Mini A1 Li, Qingxue A1 Yu, Xiaomeng PB ACM YR 2022 K1 Deep Learning K1 Defect Detection K1 Edge Computing K1 Feature Learning K1 Hardware K1 Power and energy K1 Energy distribution K1 Energy metering SP 144 OP 149 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3546000.3546022 DO https://dl.acm.org/doi/10.1145/3546000.3546022 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)