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 Dual-Path Model With Adaptive Attention for Vehicle Re-Id..:
, In:
2019 IEEE/CVF International Conference on Computer Vision (ICCV)
,
Khorramshahi, Pirazh
;
Kumar, Amit
;
Peri, Neehar
... - p. 6131-6140 , 2019
Link:
https://doi.org/10.1109/ICCV.2019.00623
RT T1
2019 IEEE/CVF International Conference on Computer Vision (ICCV)
: T1
A Dual-Path Model With Adaptive Attention for Vehicle Re-Identification
UL https://suche.suub.uni-bremen.de/peid=ieee-9010356&Exemplar=1&LAN=DE A1 Khorramshahi, Pirazh A1 Kumar, Amit A1 Peri, Neehar A1 Rambhatla, Sai Saketh A1 Chen, Jun-Cheng A1 Chellappa, Rama YR 2019 SN 2380-7504 K1 Feature extraction K1 Adaptation models K1 Heating systems K1 Estimation K1 Automobiles K1 Training K1 Task analysis SP 6131 OP 6140 LK http://dx.doi.org/https://doi.org/10.1109/ICCV.2019.00623 DO https://doi.org/10.1109/ICCV.2019.00623 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)