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
Robust Efficient License Plate and Character Detection Syst..:
, In:
Proceedings of the 2023 ACM Southeast Conference
,
He, Selena
;
Nguyen, Tu
;
Suo, Kun
- p. 104-111 , 2023
Link:
https://dl.acm.org/doi/10.1145/3564746.3587108
RT T1 <cTitle>Proceedings of the 2023 ACM Southeast Conference</cTitle>: T1 <Title>Robust Efficient License Plate and Character Detection System Based on Simplified CNN</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3587108&Exemplar=1&LAN=DE A1 He, Selena A1 Nguyen, Tu A1 Suo, Kun PB ACM YR 2023 K1 convolutional neural networks (CNN) K1 license plate recognition K1 YOLO K1 big data analytics K1 deep learning model K1 Computing methodologies K1 Machine learning K1 Machine learning approaches SP 104 OP 111 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3564746.3587108 DO https://dl.acm.org/doi/10.1145/3564746.3587108 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
