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
Recovering Accuracy of RRAM-based CIM for Binarized Neural ..:
, In:
2022 IEEE International Symposium on Circuits and Systems (ISCAS)
,
Chong, Yi Sheng
;
Goh, Wang Ling
;
Ong, Yew Soon
.. - p. 2958-2962 , 2022
Link:
https://doi.org/10.1109/ISCAS48785.2022.9937271
RT T1
2022 IEEE International Symposium on Circuits and Systems (ISCAS)
: T1
Recovering Accuracy of RRAM-based CIM for Binarized Neural Network via Chip-in-the-loop Training
UL https://suche.suub.uni-bremen.de/peid=ieee-9937271&Exemplar=1&LAN=DE A1 Chong, Yi Sheng A1 Goh, Wang Ling A1 Ong, Yew Soon A1 Nambiar, Vishnu P. A1 Do, Anh Tuan YR 2022 SN 2158-1525 K1 Resistance K1 Training K1 Neural networks K1 Resistive RAM K1 Programming K1 Writing K1 Parallel processing SP 2958 OP 2962 LK http://dx.doi.org/https://doi.org/10.1109/ISCAS48785.2022.9937271 DO https://doi.org/10.1109/ISCAS48785.2022.9937271 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)