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AI-BAQ: Deep Learning for Adaptive SAR Raw Data Quantization

Gollin, Nicola and Martone, Michele and Imbembo, Ernesto and Ghiglione, Max and Knoll, Stefan and Krieger, Gerhard and Rizzoli, Paola (2025) AI-BAQ: Deep Learning for Adaptive SAR Raw Data Quantization. IEEE Transactions on Geoscience and Remote Sensing, 63 (52206). IEEE - Institute of Electrical and Electronics Engineers. doi: 10.1109/TGRS.2025.3607089. ISSN 0196-2892.

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Official URL: https://ieeexplore.ieee.org/document/11153539


Item URL in elib:https://elib.dlr.de/209664/
Document Type:Article
Title:AI-BAQ: Deep Learning for Adaptive SAR Raw Data Quantization
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Gollin, NicolaUNSPECIFIEDhttps://orcid.org/0000-0003-0477-3273UNSPECIFIED
Martone, MicheleUNSPECIFIEDhttps://orcid.org/0000-0002-4601-6599UNSPECIFIED
Imbembo, ErnestoUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Ghiglione, MaxUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Knoll, StefanUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Krieger, GerhardUNSPECIFIEDhttps://orcid.org/0000-0002-4548-0285UNSPECIFIED
Rizzoli, PaolaUNSPECIFIEDhttps://orcid.org/0000-0001-9118-2732UNSPECIFIED
Date:8 September 2025
Journal or Publication Title:IEEE Transactions on Geoscience and Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:63
DOI:10.1109/TGRS.2025.3607089
Publisher:IEEE - Institute of Electrical and Electronics Engineers
ISSN:0196-2892
Status:Published
Keywords:SAR Raw Data Quantizaiton, Performance-Optimized Bitrate allocation, AI, Deep Learning
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:07 Nov 2025 09:54
Last Modified:07 Nov 2025 14:14

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