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

Multiclass Vessel Detection From High Resolution Optical Satellite Images Based On Deep Neural Networks

Voinov, Sergey and Heymann, Frank and Bill, Ralf and Schwarz, Egbert (2019) Multiclass Vessel Detection From High Resolution Optical Satellite Images Based On Deep Neural Networks. In: IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, pp. 166-169. Institute of Electrical and Electronics Engineers (IEEE). 2019 IEEE International Geoscience and Remote Sensing Symposium, 28 July-2 Aug. 2019, Yokohama, Japan. DOI: 10.1109/IGARSS.2019.8900506 ISBN 978-1-5386-9154-0 ISSN 2153-7003

Full text not available from this repository.

Official URL: https://ieeexplore.ieee.org/document/8900506

Abstract

One of the core components of remote sensing based maritime surveillance applications is vessel detection. It helps to prevent and investigate different unlawful actions as well as environmental hazards present at sea. Growing constellation of very high resolution (VHR) optical satellite sensors are able to frequently cover large areas with spatial resolution of up to 0.3m per pixel, which is sufficient to detect and distinguish different types of vessels. This paper presents a novel method for automatic multiclass vessel detection with use of deep convolutional neural networks (DCNN) and principle component analysis (PCA). The described approach provides reasonable performance and therefore is potentially suitable for near real time (NRT) applications.

Item URL in elib:https://elib.dlr.de/131798/
Document Type:Conference or Workshop Item (Speech)
Title:Multiclass Vessel Detection From High Resolution Optical Satellite Images Based On Deep Neural Networks
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Voinov, SergeySergey.Voinov (at) dlr.dehttps://orcid.org/0000-0003-1511-9728
Heymann, FrankFrank.Heymann (at) dlr.deUNSPECIFIED
Bill, RalfUniversity of RostockUNSPECIFIED
Schwarz, EgbertEgbert.Schwarz (at) dlr.deUNSPECIFIED
Date:14 November 2019
Journal or Publication Title:IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
DOI :10.1109/IGARSS.2019.8900506
Page Range:pp. 166-169
Publisher:Institute of Electrical and Electronics Engineers (IEEE)
ISSN:2153-7003
ISBN:978-1-5386-9154-0
Status:Published
Keywords:optical remote sensing, multiclass vessel detection, ship detection,vesselclassification, object detection, convolutional neural networks, CNN, deep learning
Event Title:2019 IEEE International Geoscience and Remote Sensing Symposium
Event Location:Yokohama, Japan
Event Type:international Conference
Event Dates:28 July-2 Aug. 2019
Organizer:IEEE GRSS
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 - Geoproducts, -systems and -services
Location: Neustrelitz
Institutes and Institutions:German Remote Sensing Data Center > National Ground Segment
Deposited By: Voinov, Sergey
Deposited On:02 Dec 2019 11:59
Last Modified:02 Dec 2019 11:59

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.