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
Boost Off/On-Manifold Adversarial Robustness for Deep Learn..:
, In:
Proceedings of the 2023 ACM Asia Conference on Computer and Communications Security
,
Huang, Mengdie
;
Xie, Yi
;
Chen, Xiaofeng
... - p. 716-730 , 2023
Link:
https://dl.acm.org/doi/10.1145/3579856.3595786
RT T1 <cTitle>Proceedings of the 2023 ACM Asia Conference on Computer and Communications Security</cTitle>: T1 <Title>Boost Off/On-Manifold Adversarial Robustness for Deep Learning with Latent Representation Mixup</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3595786&Exemplar=1&LAN=DE A1 Huang, Mengdie A1 Xie, Yi A1 Chen, Xiaofeng A1 Li, Jin A1 Dong, Changyu A1 Liu, Zheli A1 Susilo, Willy PB ACM YR 2023 K1 adversarial attack K1 adversarial robustness K1 deep neural networks K1 representation learning K1 Computing methodologies K1 Machine learning K1 Security and privacy K1 Formal methods and theory of security SP 716 OP 730 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3579856.3595786 DO https://dl.acm.org/doi/10.1145/3579856.3595786 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
