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
Uncovering the Resilience of Binarized Spiking Neural Netwo..:
, In:
2023 12th International Conference on Control, Automation and Information Sciences (ICCAIS)
,
Bui, Ngoc-My
;
Dinh, Van-Ngoc
;
Pham, Van-Hau
. - p. 674-679 , 2023
Link:
https://doi.org/10.1109/ICCAIS59597.2023.10382270
RT T1 <cTitle>2023 12th International Conference on Control, Automation and Information Sciences (ICCAIS)</cTitle>: T1 <Title>Uncovering the Resilience of Binarized Spiking Neural Networks under Adversarial Attacks</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10382270&Exemplar=1&LAN=DE A1 Bui, Ngoc-My A1 Dinh, Van-Ngoc A1 Pham, Van-Hau A1 Trinh, Quang-Kien YR 2023 SN 2475-7896 K1 Training K1 Automation K1 Computer architecture K1 Color K1 Artificial neural networks K1 Robustness K1 Hardware K1 Binarized Spiking Neural Networks K1 Adversarial Attacks K1 Adversarial Training SP 674 OP 679 LK http://dx.doi.org/https://doi.org/10.1109/ICCAIS59597.2023.10382270 DO https://doi.org/10.1109/ICCAIS59597.2023.10382270 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
