Exploiting Artificial Intelligence for Performance-Optimized Raw Data Quantization in InSAR Systems

Martone, Michele and Gollin, Nicola and Rizzoli, Paola and Krieger, Gerhard (2023) Exploiting Artificial Intelligence for Performance-Optimized Raw Data Quantization in InSAR Systems. In: FRINGE Online Abstracts. ESA FRINGE Workshop, 2023-09-11 - 2013-09-15, Leeds, UK.

PDF
84kB

Item URL in elib:

https://elib.dlr.de/196380/

Document Type:

Conference or Workshop Item (Speech)

Title:

Exploiting Artificial Intelligence for Performance-Optimized Raw Data Quantization in InSAR Systems

Authors:

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

Date:

2023

Journal or Publication Title:

FRINGE Online Abstracts

Refereed publication:

Yes

Open Access:

Yes

Gold Open Access:

In SCOPUS:

In ISI Web of Science:

Status:

Published

Keywords:

Synthetic Aperture Radar, Quantization, Machine Learning

Event Title:

ESA FRINGE Workshop

Event Location:

Leeds, UK

Event Type:

international Conference

Event Start Date:

11 September 2023

Event End Date:

15 September 2013

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 - TerraSAR/TanDEM

Location:

Oberpfaffenhofen

Institutes and Institutions:

Microwaves and Radar Institute > Spaceborne SAR Systems
Microwaves and Radar Institute > Radar Concepts

Deposited By:

Martone, Michele

Deposited On:

02 Aug 2023 13:58

Last Modified:

24 Apr 2024 20:56

Repository Staff Only: item control page