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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, 2018-07-22 - 2018-07-27, 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/ | ||||||||||||||||
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| Document Type: | Conference or Workshop Item (Poster) | ||||||||||||||||
| Title: | Towards Automated Vessel Detection and Type Recognition from VHR Optical Satellite Images | ||||||||||||||||
| Authors: |
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| 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 Start Date: | 22 July 2018 | ||||||||||||||||
| Event End Date: | 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 - Earth Observation | ||||||||||||||||
| DLR - Research theme (Project): | R - Geoproducts and systems, 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: | 24 Apr 2024 20:27 |
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