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
Deep Graph Convolutional Networks for Incident-Driven Traff..:
, In:
Proceedings of the 29th ACM International Conference on Information & Knowledge Management
,
Xie, Qinge
;
Guo, Tiancheng
;
Chen, Yang
... - p. 1665-1674 , 2020
Link:
https://dl.acm.org/doi/10.1145/3340531.3411873
RT T1
Proceedings of the 29th ACM International Conference on Information & Knowledge Management
: T1
Deep Graph Convolutional Networks for Incident-Driven Traffic Speed Prediction
UL https://suche.suub.uni-bremen.de/peid=acm-3411873&Exemplar=1&LAN=DE A1 Xie, Qinge A1 Guo, Tiancheng A1 Chen, Yang A1 Xiao, Yu A1 Wang, Xin A1 Zhao, Ben Y. PB ACM YR 2020 K1 deep neural network K1 real-time traffic prediction K1 time series K1 traffic incidents K1 Information systems K1 Information systems applications K1 Spatial-temporal systems K1 Data mining SP 1665 OP 1674 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3340531.3411873 DO https://dl.acm.org/doi/10.1145/3340531.3411873 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)