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 pedestrian detection method based on PSO and multimodal f..:
, In:
2016 Chinese Control and Decision Conference (CCDC)
,
Li, Wei-Xing
;
Ma, We-Liang
;
Quan, Bing
.. - p. 6054-6058 , 2016
Link:
https://doi.org/10.1109/CCDC.2016.7532083
RT T1
2016 Chinese Control and Decision Conference (CCDC)
: T1
A pedestrian detection method based on PSO and multimodal function
UL https://suche.suub.uni-bremen.de/peid=ieee-7532083&Exemplar=1&LAN=DE A1 Li, Wei-Xing A1 Ma, We-Liang A1 Quan, Bing A1 Pei, Meng-xin A1 Feng, Xiao-xue YR 2016 SN 1948-9447 K1 Feature extraction K1 Dictionaries K1 Acceleration K1 Encoding K1 Training K1 Support vector machines K1 Particle swarm optimization K1 Pedestrian detection K1 Sparse coding K1 PSO K1 Multimodal function SP 6054 OP 6058 LK http://dx.doi.org/https://doi.org/10.1109/CCDC.2016.7532083 DO https://doi.org/10.1109/CCDC.2016.7532083 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)