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
Energy-Efficient and High-Throughput CNN Inference Engine B..:
Islam, Md. Najrul
;
Shrestha, Rahul
;
Chowdhury, Shubhajit Roy
IEEE Transactions on Circuits and Systems I: Regular Papers. 71 (2024) 7 - p. 3189-3202 , 2024
Link:
https://doi.org/10.1109/tcsi.2024.3392807
RT Journal T1 <Title>Energy-Efficient and High-Throughput CNN Inference Engine Based on Memory-Sharing and Data-Reusing for Edge Applications</Title> UL https://suche.suub.uni-bremen.de/peid=cr-10.1109_tcsi.2024.3392807&Exemplar=1&LAN=DE A1 Islam, Md. Najrul A1 Shrestha, Rahul A1 Chowdhury, Shubhajit Roy PB Institute of Electrical and Electronics Engineers (IEEE) YR 2024 SN 1549-8328 SN 1558-0806 JF IEEE Transactions on Circuits and Systems I: Regular Papers VO 71 IS 7 SP 3189 OP 3202 LK http://dx.doi.org/https://doi.org/10.1109/tcsi.2024.3392807 DO https://doi.org/10.1109/tcsi.2024.3392807 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
