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
A 0.59μJ/pixel High-throughput Energy-efficient Neural Volu..:
, In:
2024 IEEE Custom Integrated Circuits Conference (CICC)
,
Yuan, Zhechen
;
Yuan, Binzhe
;
Gu, Yuhan
... - p. 1-2 , 2024
Link:
https://doi.org/10.1109/CICC60959.2024.10529071
RT T1
2024 IEEE Custom Integrated Circuits Conference (CICC)
: T1
A 0.59μJ/pixel High-throughput Energy-efficient Neural Volume Rendering Accelerator on FPGA
UL https://suche.suub.uni-bremen.de/peid=ieee-10529071&Exemplar=1&LAN=DE A1 Yuan, Zhechen A1 Yuan, Binzhe A1 Gu, Yuhan A1 Zheng, Yueyang A1 He, Yunxiang A1 Wang, Xuexin A1 Rao, Chaolin A1 Zhou, Pingqiang A1 Yu, Jingyi A1 Lou, Xin YR 2024 SN 2152-3630 K1 Application specific integrated circuits K1 Computational modeling K1 Rendering (computer graphics) K1 Hardware K1 Explosives K1 Energy efficiency K1 Convolutional neural networks SP 1 OP 2 LK http://dx.doi.org/https://doi.org/10.1109/CICC60959.2024.10529071 DO https://doi.org/10.1109/CICC60959.2024.10529071 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)