Login
EN
[EN] English
[FR] Français
Login
EN
[EN] English
[FR] Français
Give us feedback
Search and explore
Search
Explore ORBilu
Open Science
Open Science
Open Access
Research Data Management
Definitions
OS Working group
Open Access Week 24
Statistics
Help
User Guide
FAQ
Publication list
Document types
Reporting
Training
Legal Information
Data protection
Legal notices
About
About ORBilu
Deposit Mandate
ORBilu team
Impact and visibility
About statistics
About metrics
OAI-PMH
Project history
Back
Home
Detailled Reference
No full text
Scientific presentation in universities or research centers (Scientific presentations in universities or research centers)
Deep Learning-based Image Enhancement for Space Applications
ORTIZ DEL CASTILLO, Miguel
;
MOHAMED ALI, Mohamed Adel
;
JAMROZIK, Michele Lynn
et al.
2021
Permalink
https://hdl.handle.net/10993/50508
Files (0)
Send to
Details
Statistics
Bibliography
Similar publications
Files
Full Text
No document available.
Send to
RIS
BibTex
APA
Chicago
Permalink
X
Linkedin
copy to clipboard
copied
Details
Disciplines :
Computer science
Author, co-author :
ORTIZ DEL CASTILLO, Miguel
;
University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > CVI2
MOHAMED ALI, Mohamed Adel
;
University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > CVI2
JAMROZIK, Michele Lynn
;
University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > CVI2
GAUDILLIERE, Vincent
;
University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > CVI2
AOUADA, Djamila
;
University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > CVI2
Language :
English
Title :
Deep Learning-based Image Enhancement for Space Applications
Publication date :
September 2021
Event name :
ESA EO Φ-WEEK
Event date :
from 11-10-2021 to 15-10-2021
Audience :
International
Additional URL :
https://www.youtube.com/watch?v=msylPDOKpvA
Available on ORBilu :
since 07 March 2022
Statistics
Number of views
217 (42 by Unilu)
Number of downloads
0 (0 by Unilu)
More statistics
Bibliography
Similar publications
Contact ORBilu