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 method of intrusion detection based on Attention-LSTM neu..:
, In:
Proceedings of the 2020 5th International Conference on Machine Learning Technologies
,
Yang, Shuaichuang
;
Tan, Minsheng
;
Xia, Shiying
. - p. 46-50 , 2020
Link:
https://dl.acm.org/doi/10.1145/3409073.3409096
RT T1
Proceedings of the 2020 5th International Conference on Machine Learning Technologies
: T1
A method of intrusion detection based on Attention-LSTM neural network
UL https://suche.suub.uni-bremen.de/peid=acm-3409096&Exemplar=1&LAN=DE A1 Yang, Shuaichuang A1 Tan, Minsheng A1 Xia, Shiying A1 Liu, Fangju PB ACM YR 2020 K1 Attention machine K1 Deep learning K1 Intrusion detection K1 LSTM K1 Security and privacy K1 Intrusion/anomaly detection and malware mitigation K1 Intrusion detection systems SP 46 OP 50 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3409073.3409096 DO https://dl.acm.org/doi/10.1145/3409073.3409096 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)