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
Fiber-optics IoT healthcare system based on deep reinforcem..:
Lakhan, Abdullah
;
Nedoma, Jan
;
Mohammed, Mazin Abed
...
Computers in Biology and Medicine. 178 (2024) - p. 108694 , 2024
Link:
https://doi.org/10.1016/j.compbiomed.2024.108694
RT Journal T1
Fiber-optics IoT healthcare system based on deep reinforcement learning combinatorial constraint scheduling for hybrid telemedicine applications
UL https://suche.suub.uni-bremen.de/peid=cr-10.1016_j.compbiomed.2024.108694&Exemplar=1&LAN=DE A1 Lakhan, Abdullah A1 Nedoma, Jan A1 Mohammed, Mazin Abed A1 Deveci, Muhammet A1 Fajkus, Marcel A1 Marhoon, Haydar Abdulameer A1 Memon, Sajida A1 Martinek, Radek PB Elsevier BV YR 2024 SN 0010-4825 JF Computers in Biology and Medicine VO 178 SP 108694 LK http://dx.doi.org/https://doi.org/10.1016/j.compbiomed.2024.108694 DO https://doi.org/10.1016/j.compbiomed.2024.108694 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)