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
SVM binary classifier ensembles for image classification:
, In:
Proceedings of the tenth international conference on Information and knowledge management
,
Goh, King-Shy
;
Chang, Edward
;
Cheng, Kwang-Ting
- p. 395-402 , 2001
Link:
https://dl.acm.org/doi/10.1145/502585.502652
RT T1 <cTitle>Proceedings of the tenth international conference on Information and knowledge management</cTitle>: T1 <Title>SVM binary classifier ensembles for image classification</Title> UL https://suche.suub.uni-bremen.de/peid=acm-502652&Exemplar=1&LAN=DE A1 Goh, King-Shy A1 Chang, Edward A1 Cheng, Kwang-Ting PB ACM YR 2001 K1 Computing methodologies K1 Machine learning K1 Machine learning algorithms K1 Feature selection K1 Theory of computation K1 Randomness, geometry and discrete structures K1 Error-correcting codes K1 Artificial intelligence K1 Computer vision K1 Computer vision representations SP 395 OP 402 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/502585.502652 DO https://dl.acm.org/doi/10.1145/502585.502652 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
