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
Deep Residual Network of Spectral and Spatial Fusion for Hy..:
, In:
2019 IEEE Fifth International Conference on Multimedia Big Data (BigMM)
,
Han, Xian-Hua
;
Chen, Yen-Wei
- p. 266-270 , 2019
Link:
https://doi.org/10.1109/BigMM.2019.00-13
RT T1
2019 IEEE Fifth International Conference on Multimedia Big Data (BigMM)
: T1
Deep Residual Network of Spectral and Spatial Fusion for Hyperspectral Image Super-Resolution
UL https://suche.suub.uni-bremen.de/peid=ieee-8919399&Exemplar=1&LAN=DE A1 Han, Xian-Hua A1 Chen, Yen-Wei YR 2019 K1 Spatial resolution K1 Image reconstruction K1 Hyperspectral imaging K1 Databases K1 Signal resolution K1 Hyperspectral reconstruction, residual network, deep learning, ResNet, spatial and spectral fusion SP 266 OP 270 LK http://dx.doi.org/https://doi.org/10.1109/BigMM.2019.00-13 DO https://doi.org/10.1109/BigMM.2019.00-13 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)