elib
DLR-Header
DLR-Logo -> http://www.dlr.de
DLR Portal Home | Imprint | Privacy Policy | Contact | Deutsch
Fontsize: [-] Text [+]

Deep Learning Solutions for TanDEM-X based forest classification

Mazza, Antonio and Sica, Francescopaolo (2019) Deep Learning Solutions for TanDEM-X based forest classification. 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:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Mazza, AntonioUniversity of Naples Federico IIUNSPECIFIED
Sica, FrancescopaoloFrancescopaolo.Sica (at) dlr.dehttps://orcid.org/0000-0003-1593-1492
Date:2019
Refereed publication:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Accepted
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 Dates:2019-07-28 -2019-08-02
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - SAR-Methodology
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:09 Apr 2019 07:30

Repository Staff Only: item control page

Browse
Search
Help & Contact
Information
electronic library is running on EPrints 3.3.12
Copyright © 2008-2017 German Aerospace Center (DLR). All rights reserved.