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
An Embedded Deep Learning Object Detection Model For Traffi..:
, In:
2020 IEEE International Conference on Multimedia & Expo Workshops (ICMEW)
,
Chen, Weiju
;
Wu, WanChen
;
Chang, Hao-Wei
... - p. 1-5 , 2020
Link:
https://doi.org/10.1109/ICMEW46912.2020.9105994
RT T1 <cTitle>2020 IEEE International Conference on Multimedia & Expo Workshops (ICMEW)</cTitle>: T1 <Title>An Embedded Deep Learning Object Detection Model For Traffic In Asian Countries</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9105994&Exemplar=1&LAN=DE A1 Chen, Weiju A1 Wu, WanChen A1 Chang, Hao-Wei A1 Lin, Wei-Liang A1 Yang, Changhua A1 Liu, Yang-wei YR 2020 K1 object detection K1 deep learning K1 lightweight K1 embedded systems K1 YOLO v3 SP 1 OP 5 LK http://dx.doi.org/https://doi.org/10.1109/ICMEW46912.2020.9105994 DO https://doi.org/10.1109/ICMEW46912.2020.9105994 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
