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 Adaptable Real-Time Object Detection for Traffic Surveil..:
, In:
2022 International Conference on Business Analytics for Technology and Security (ICBATS)
,
Vinod, G.
;
Padmapriya, G.
- p. 1-4 , 2022
Link:
https://doi.org/10.1109/ICBATS54253.2022.9759030
RT T1 <cTitle>2022 International Conference on Business Analytics for Technology and Security (ICBATS)</cTitle>: T1 <Title>An Adaptable Real-Time Object Detection for Traffic Surveillance using R-CNN over CNN with Improved Accuracy</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9759030&Exemplar=1&LAN=DE A1 Vinod, G. A1 Padmapriya, G. YR 2022 K1 Training K1 Surveillance K1 Object detection K1 Traffic control K1 Real-time systems K1 Convolutional neural networks K1 Security K1 Machine learning K1 Novel R-CNN K1 CNN K1 Real Time objects K1 Traffic Surveillance SP 1 OP 4 LK http://dx.doi.org/https://doi.org/10.1109/ICBATS54253.2022.9759030 DO https://doi.org/10.1109/ICBATS54253.2022.9759030 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
