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2 - A brief introduction to deep learning

Hänsch, Ronny and Schmitt, Michael (2026) 2 - A brief introduction to deep learning. In: Deep Learning for Synthetic Aperture Radar Remote Sensing Elsevier. pp. 25-52. doi: 10.1016/B978-0-44-336344-3.00007-6. ISBN 9780443363443.

Full text not available from this repository.

Official URL: https://www.sciencedirect.com/science/article/pii/B9780443363443000076

Abstract

This chapter introduces Deep Learning (DL) as a transformative paradigm in remote sensing, particularly in the context of Synthetic Aperture Radar (SAR) data. While traditional methods — from manual interpretation to physically inspired models — remain important, DL is increasingly integrated into operational workflows. The chapter offers a high-level overview of core DL concepts as a foundation for later chapters focused on SAR applications. Supported by open datasets and tools, DL is rapidly advancing applied SAR domains including disaster response, climate monitoring, and land use analysis.

Item URL in elib:https://elib.dlr.de/225457/
Document Type:Book Section
Title:2 - A brief introduction to deep learning
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Hänsch, RonnyRonny.Haensch (at) dlr.dehttps://orcid.org/0000-0002-2936-6765UNSPECIFIED
Schmitt, MichaelUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Date:2026
Journal or Publication Title:Deep Learning for Synthetic Aperture Radar Remote Sensing
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
DOI:10.1016/B978-0-44-336344-3.00007-6
Page Range:pp. 25-52
Publisher:Elsevier
ISBN:9780443363443
Status:Published
Keywords:Machine learning, Deep learning, Artificial neural network, Convolutional neural network (CNN)
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 - Artificial Intelligence
Location: Oberpfaffenhofen
Institutes and Institutions:Microwaves and Radar Institute > SAR Technology
Deposited By: Hänsch, Ronny
Deposited On:03 Jul 2026 15:27
Last Modified:06 Jul 2026 12:17

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