AI-BASED PERFORMANCE-OPTIMIZED QUANTIZATION FOR FUTURE SAR SYSTEMS

Gollin, Nicola and Martone, Michele and Krieger, Gerhard and Rizzoli, Paola (2023) AI-BASED PERFORMANCE-OPTIMIZED QUANTIZATION FOR FUTURE SAR SYSTEMS. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2023-07-16 - 2023-07-21, Pasadena, California, USA.

PDF - Only accessible within DLR
2MB

Item URL in elib:

https://elib.dlr.de/194840/

Document Type:

Conference or Workshop Item (Speech)

Title:

AI-BASED PERFORMANCE-OPTIMIZED QUANTIZATION FOR FUTURE SAR SYSTEMS

Authors:

Authors	Institution or Email of Authors	Author's ORCID iD	ORCID Put Code
Gollin, Nicola	UNSPECIFIED	https://orcid.org/0000-0003-0477-3273	UNSPECIFIED
Martone, Michele	UNSPECIFIED	https://orcid.org/0000-0002-4601-6599	UNSPECIFIED
Krieger, Gerhard	UNSPECIFIED	https://orcid.org/0000-0002-4548-0285	UNSPECIFIED
Rizzoli, Paola	UNSPECIFIED	https://orcid.org/0000-0001-9118-2732	UNSPECIFIED

Date:

2023

Refereed publication:

Yes

Open Access:

Gold Open Access:

In SCOPUS:

In ISI Web of Science:

Status:

Published

Keywords:

SAR Raw Data Compression, AI, Deep Learning, Data Volume Reduction

Event Title:

IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

Event Location:

Pasadena, California, USA

Event Type:

international Conference

Event Dates:

2023-07-16 - 2023-07-21

HGF - Research field:

Aeronautics, Space and Transport

HGF - Program:

Space

HGF - Program Themes:

Earth Observation

DLR - Research area:

Raumfahrt

DLR - Program:

R EO - Earth Observation

DLR - Research theme (Project):

R - AI4SAR

Location:

Oberpfaffenhofen

Institutes and Institutions:

Microwaves and Radar Institute > Spaceborne SAR Systems

Deposited By:

Gollin, Nicola

Deposited On:

02 May 2023 10:41

Last Modified:

30 Nov 2023 12:42

Repository Staff Only: item control page