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
Contour Accentuation for Transfer Learning-Based Ship Recog..:
, In:
Companion Proceedings of the Web Conference 2020
,
Chen, Chi-Hua
;
Zhang, Yizhuo
;
Guo, Wenzhong
... - p. 61-62 , 2020
Link:
https://dl.acm.org/doi/10.1145/3366424.3382697
RT T1
Companion Proceedings of the Web Conference 2020
: T1
Contour Accentuation for Transfer Learning-Based Ship Recognition Method
UL https://suche.suub.uni-bremen.de/peid=acm-3382697&Exemplar=1&LAN=DE A1 Chen, Chi-Hua A1 Zhang, Yizhuo A1 Guo, Wenzhong A1 Pan, Mingyang A1 Lyu, Lingjuan A1 Lin, Chia-Yu PB ACM YR 2020 K1 contour accentuation K1 convolutional neural network K1 ship recognition K1 transfer learning K1 Computing methodologies K1 Applied computing K1 Artificial intelligence K1 Machine learning K1 Physical sciences and engineering K1 Computer vision K1 Learning paradigms K1 Machine learning approaches K1 Classification and regression trees K1 Neural networks SP 61 OP 62 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3366424.3382697 DO https://dl.acm.org/doi/10.1145/3366424.3382697 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)