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
NV-BNN : An Accurate Deep Convolutional Neural Network B..:
, In:
Proceedings of the 56th Annual Design Automation Conference 2019
,
Chang, Chih-Cheng
;
Wu, Ming-Hung
;
Lin, Jia-Wei
... - p. 1-6 , 2019
Link:
https://dl.acm.org/doi/10.1145/3316781.3317872
RT T1
Proceedings of the 56th Annual Design Automation Conference 2019
: T1
NV-BNN : An Accurate Deep Convolutional Neural Network Based on Binary STT-MRAM for Adaptive AI Edge
UL https://suche.suub.uni-bremen.de/peid=acm-3317872&Exemplar=1&LAN=DE A1 Chang, Chih-Cheng A1 Wu, Ming-Hung A1 Lin, Jia-Wei A1 Li, Chun-Hsien A1 Parmar, Vivek A1 Lee, Heng-Yuan A1 Wei, Jeng-Hua A1 Sheu, Shyh-Shyuan A1 Suri, Manan A1 Chang, Tian-Sheuan A1 Hou, Tuo-Hung PB ACM YR 2019 K1 Computing methodologies K1 Machine learning K1 Machine learning approaches SP 1 OP 6 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3316781.3317872 DO https://dl.acm.org/doi/10.1145/3316781.3317872 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)