Deep Learning Solutions for TanDEM-X based forest classification

Mazza, Antonio and Sica, Francescopaolo (2019) Deep Learning Solutions for TanDEM-X based forest classification. In: International Geoscience and Remote Sensing Symposium (IGARSS). IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2019-07-28 - 2019-08-02, Yokohama, Japan.

Full text not available from this repository.

Item URL in elib:

https://elib.dlr.de/127105/

Document Type:

Conference or Workshop Item (Poster)

Title:

Deep Learning Solutions for TanDEM-X based forest classification

Authors:

Authors	Institution or Email of Authors	Author's ORCID iD	ORCID Put Code
Mazza, Antonio	University of Naples Federico II	UNSPECIFIED	UNSPECIFIED
Sica, Francescopaolo	UNSPECIFIED	https://orcid.org/0000-0003-1593-1492	UNSPECIFIED

Date:

2019

Journal or Publication Title:

International Geoscience and Remote Sensing Symposium (IGARSS)

Refereed publication:

Yes

Open Access:

Gold Open Access:

In SCOPUS:

Yes

In ISI Web of Science:

Status:

Published

Keywords:

Forest classification, InSAR, TanDEM-X, Deep Learning, Convolutional Neural Networks

Event Title:

IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

Event Location:

Yokohama, Japan

Event Type:

international Conference

Event Start Date:

28 July 2019

Event End Date:

2 August 2019

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 - SAR methods

Location:

Oberpfaffenhofen

Institutes and Institutions:

Microwaves and Radar Institute > Spaceborne SAR Systems

Deposited By:

Sica, Dr. Francescopaolo

Deposited On:

09 Apr 2019 07:30

Last Modified:

24 Apr 2024 20:30

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