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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, 2019-07-28 - 2019-08-02, Yokohama, Japan. doi: 10.1109/IGARSS.2019.8900506. ISBN 978-1-5386-9154-0. ISSN 2153-7003.
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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/ | ||||||||||||||||||||
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| Document Type: | Conference or Workshop Item (Speech) | ||||||||||||||||||||
| Title: | Multiclass Vessel Detection From High Resolution Optical Satellite Images Based On Deep Neural Networks | ||||||||||||||||||||
| Authors: |
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| 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 Start Date: | 28 July 2019 | ||||||||||||||||||||
| Event End Date: | 2 August 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 - 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: | 02 Dec 2019 11:59 | ||||||||||||||||||||
| Last Modified: | 17 Jul 2025 09:25 |
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