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
Machine learning-based energy consumption modeling and comp..:
Sharrab, Yousef O.
;
Alsmirat, Mohammad
;
Hawashin, Bilal
.
International Journal of Electrical and Computer Engineering (IJECE). 11 (2021) 2 - p. 1303 , 2021
Link:
https://doi.org/10.11591/ijece.v11i2.pp1303-1310
RT Journal T1
Machine learning-based energy consumption modeling and comparison of H.264/AVC and google VP8 encoders
UL https://suche.suub.uni-bremen.de/peid=cr-10.11591_ijece.v11i2.pp1303-1310&Exemplar=1&LAN=DE A1 Sharrab, Yousef O. A1 Alsmirat, Mohammad A1 Hawashin, Bilal A1 Sarhan, Nabil PB Institute of Advanced Engineering and Science YR 2021 SN 2722-2578 SN 2088-8708 JF International Journal of Electrical and Computer Engineering (IJECE) VO 11 IS 2 SP 1303 LK http://dx.doi.org/https://doi.org/10.11591/ijece.v11i2.pp1303-1310 DO https://doi.org/10.11591/ijece.v11i2.pp1303-1310 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)