Deep Learning; Neural Network Compression; Edge Devices
Abstract :
[en] Efficient compression techniques are required to deploy deep neural networks (DNNs) on edge devices for space resource utilization tasks. Two approaches are investigated.
Research center :
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > CVI² - Computer Vision Imaging & Machine Intelligence
Disciplines :
Space science, astronomy & astrophysics Computer science Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
SHNEIDER, Carl ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > CVI2
SINHA, Nilotpal ; 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
ASTRID, Marcella ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > CVI2
ROSTAMI ABENDANSARI, Peyman ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > CVI2
KACEM, Anis ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > CVI2
SHABAYEK, Abd El Rahman ; 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
External co-authors :
no
Language :
English
Title :
Compression of Deep Neural Networks for Space Autonomous Systems
Publication date :
19 April 2023
Number of pages :
A0
Event name :
Luxembourg Space Resources Week 2023
Event place :
Luxembourg, Luxembourg
Event date :
19-04-2023 to 21-04-2023
Audience :
International
Focus Area :
Security, Reliability and Trust Computational Sciences
