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
Deep Learning Predicts Ar/O2 Plasma in Inductively Coupled ..:
Lee, Sang-Bin
;
Kim, Ji-Hoon
;
Kim, Gwan
...
Applied Science and Convergence Technology. 32 (2023) 5 - p. 122-126 , 2023
Link:
https://doi.org/10.5757/asct.2023.32.5.122
RT Journal T1 <Title>Deep Learning Predicts Ar/O2 Plasma in Inductively Coupled Plasma Discharge</Title> UL https://suche.suub.uni-bremen.de/peid=cr-10.5757_asct.2023.32.5.122&Exemplar=1&LAN=DE A1 Lee, Sang-Bin A1 Kim, Ji-Hoon A1 Kim, Gwan A1 Park, Jun-Woo A1 Chae, Byung-Kwan A1 Choe, Hee-Hwan PB The Korean Vacuum Society YR 2023 SN 2288-6559 JF Applied Science and Convergence Technology VO 32 IS 5 SP 122 OP 126 LK http://dx.doi.org/https://doi.org/10.5757/asct.2023.32.5.122 DO https://doi.org/10.5757/asct.2023.32.5.122 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
