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DEDNet: Offshore Eddy Detection and Location with HF Radar by Deep Learning

Oceanic eddy is a common natural phenomenon that has large influence on human activities, and the measurement and detection of offshore eddies are significant for oceanographic research. The previous classical detecting methods, such as the Okubo–Weiss algorithm (OW), vector geometry algorithm (VG),...

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Detalles Bibliográficos
Autores principales: Liu, Fangyuan, Zhou, Hao, Wen, Biyang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7795546/
https://www.ncbi.nlm.nih.gov/pubmed/33379154
http://dx.doi.org/10.3390/s21010126
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author Liu, Fangyuan
Zhou, Hao
Wen, Biyang
author_facet Liu, Fangyuan
Zhou, Hao
Wen, Biyang
author_sort Liu, Fangyuan
collection PubMed
description Oceanic eddy is a common natural phenomenon that has large influence on human activities, and the measurement and detection of offshore eddies are significant for oceanographic research. The previous classical detecting methods, such as the Okubo–Weiss algorithm (OW), vector geometry algorithm (VG), and winding angles algorithm (WA), not only depend on expert’s experiences to set an accurate threshold, but also need heavy calculations for large detection regions. Differently from the previous works, this paper proposes a deep eddy detection neural network with pixel segmentation skeleton on high frequency radar (HFR) data, namely, the deep eddy detection network (DEDNet). An offshore eddy detection dataset is firstly constructed, which has origins from the sea surface current data measured by two HFR systems on the South China Sea. Then, a spatial globally optimum and strong detail-distinguishing pixel segmentation network is presented to automatically detect and localize offshore eddies in a flow chart. An eddy detection network based on fully convolutional networks (FCN) is also presented for comparison with DEDNet. Experimental results show that DEDNet performs better than the FCN-based eddy detection network and is competitive with the classical statistics-based methods.
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spelling pubmed-77955462021-01-10 DEDNet: Offshore Eddy Detection and Location with HF Radar by Deep Learning Liu, Fangyuan Zhou, Hao Wen, Biyang Sensors (Basel) Article Oceanic eddy is a common natural phenomenon that has large influence on human activities, and the measurement and detection of offshore eddies are significant for oceanographic research. The previous classical detecting methods, such as the Okubo–Weiss algorithm (OW), vector geometry algorithm (VG), and winding angles algorithm (WA), not only depend on expert’s experiences to set an accurate threshold, but also need heavy calculations for large detection regions. Differently from the previous works, this paper proposes a deep eddy detection neural network with pixel segmentation skeleton on high frequency radar (HFR) data, namely, the deep eddy detection network (DEDNet). An offshore eddy detection dataset is firstly constructed, which has origins from the sea surface current data measured by two HFR systems on the South China Sea. Then, a spatial globally optimum and strong detail-distinguishing pixel segmentation network is presented to automatically detect and localize offshore eddies in a flow chart. An eddy detection network based on fully convolutional networks (FCN) is also presented for comparison with DEDNet. Experimental results show that DEDNet performs better than the FCN-based eddy detection network and is competitive with the classical statistics-based methods. MDPI 2020-12-28 /pmc/articles/PMC7795546/ /pubmed/33379154 http://dx.doi.org/10.3390/s21010126 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Liu, Fangyuan
Zhou, Hao
Wen, Biyang
DEDNet: Offshore Eddy Detection and Location with HF Radar by Deep Learning
title DEDNet: Offshore Eddy Detection and Location with HF Radar by Deep Learning
title_full DEDNet: Offshore Eddy Detection and Location with HF Radar by Deep Learning
title_fullStr DEDNet: Offshore Eddy Detection and Location with HF Radar by Deep Learning
title_full_unstemmed DEDNet: Offshore Eddy Detection and Location with HF Radar by Deep Learning
title_short DEDNet: Offshore Eddy Detection and Location with HF Radar by Deep Learning
title_sort dednet: offshore eddy detection and location with hf radar by deep learning
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7795546/
https://www.ncbi.nlm.nih.gov/pubmed/33379154
http://dx.doi.org/10.3390/s21010126
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