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Towards Automated Vessel Detection and Type Recognition from VHR Optical Satellite Images

Voinov, Sergey and Krause, Detmar and Schwarz, Egbert (2018) Towards Automated Vessel Detection and Type Recognition from VHR Optical Satellite Images. In: IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, pp. 4823-4826. Institute of Electrical and Electronics Engineers (IEEE). 2018 IEEE International Geoscience and Remote Sensing Symposium, 22-27 July 2018, Valencia, Spain. DOI: 10.1109/IGARSS.2018.8519121 ISBN 978-1-5386-7150-4 ISSN 2153-7003

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Official URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8519121&isnumber=8517275

Abstract

Vessel detection and type recognition is crucial in any maritime surveillance application. This component aims at preventing or investigating unlawful actions present at sea. Modern very high resolution (VHR) optical satellite sensors are able to capture images with spatial resolution up to 0.3m per pixel, which is sufficient to distinguish ship features such as bridge position, cranes, landing pads and many others and thus possible to differentiate ship types. This paper presents a new method for automatic vessel detection and type recognition based on fusion of deep convolutional neural network architectures (CNN), which has potential for near-real time (NRT) applications.

Item URL in elib:https://elib.dlr.de/123852/
Document Type:Conference or Workshop Item (Poster)
Title:Towards Automated Vessel Detection and Type Recognition from VHR Optical Satellite Images
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Voinov, SergeySergey.Voinov (at) dlr.dehttps://orcid.org/0000-0003-1511-9728
Krause, DetmarDetmar.Krause (at) dlr.deUNSPECIFIED
Schwarz, EgbertEgbert.Schwarz (at) dlr.deUNSPECIFIED
Date:5 November 2018
Journal or Publication Title:IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
DOI :10.1109/IGARSS.2018.8519121
Page Range:pp. 4823-4826
Publisher:Institute of Electrical and Electronics Engineers (IEEE)
ISSN:2153-7003
ISBN:978-1-5386-7150-4
Status:Published
Keywords:Marine vehicles;Task analysis;Training;Object detection;Satellites;Optical sensors;Convolutional neural networks;optical remote sensing;vessel detection;vessel type recognition;object detection;object classification;convolutional neural networks;CNN;deep learning
Event Title:2018 IEEE International Geoscience and Remote Sensing Symposium
Event Location:Valencia, Spain
Event Type:international Conference
Event Dates:22-27 July 2018
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:03 Dec 2018 13:25
Last Modified:19 Feb 2019 09:52

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