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 Structured Dictionary Learning For Block Sparse Repr..:
, In:
2020 IEEE International Conference on Image Processing (ICIP)
,
Seghouane, Abd-Krim
- p. 843-847 , 2020
Link:
https://doi.org/10.1109/ICIP40778.2020.9190984
RT T1 <cTitle>2020 IEEE International Conference on Image Processing (ICIP)</cTitle>: T1 <Title>Robust Structured Dictionary Learning For Block Sparse Representations Using α-Divergence</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9190984&Exemplar=1&LAN=DE A1 Seghouane, Abd-Krim YR 2020 SN 2381-8549 K1 Dictionaries K1 Machine learning K1 Robustness K1 Sparse matrices K1 Approximation algorithms K1 Cost function K1 Encoding K1 Dictionary learning K1 block sparse representation K1 robust SP 843 OP 847 LK http://dx.doi.org/https://doi.org/10.1109/ICIP40778.2020.9190984 DO https://doi.org/10.1109/ICIP40778.2020.9190984 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
