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
Lane Detection Using Deep Learning Approach:
, In:
2022 1st International Conference on Computational Science and Technology (ICCST)
,
A, Shyam Immanuel
;
R, Kaladevi
;
Shanmugasundaram, Hariharan
... - p. 945-949 , 2022
Link:
https://doi.org/10.1109/ICCST55948.2022.10040402
RT T1 <cTitle>2022 1st International Conference on Computational Science and Technology (ICCST)</cTitle>: T1 <Title>Lane Detection Using Deep Learning Approach</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10040402&Exemplar=1&LAN=DE A1 A, Shyam Immanuel A1 R, Kaladevi A1 Shanmugasundaram, Hariharan A1 A, Bhanu prasad A1 R, Karthikeyan A1 J, Mohammad Bilal YR 2022 K1 Deep learning K1 Training K1 Lane detection K1 Convolution K1 Roads K1 Vehicle detection K1 Transforms K1 Convolution Neural Network K1 mask filtering K1 thresholding K1 LANE detection K1 Binarization SP 945 OP 949 LK http://dx.doi.org/https://doi.org/10.1109/ICCST55948.2022.10040402 DO https://doi.org/10.1109/ICCST55948.2022.10040402 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
