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Vessel detection and classification from spaceborne optical images: A literature survey
• A review of 119 papers on ship detection and classification from optical satellite. • From 1978 to March 2017, showing an exponential growth in the number of papers. • Most published methods have very limited validation. • While big steps have been made, automatic algorithms are still far from per...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Elsevier Pub. Co
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5877374/ https://www.ncbi.nlm.nih.gov/pubmed/29622842 http://dx.doi.org/10.1016/j.rse.2017.12.033 |
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author | Kanjir, Urška Greidanus, Harm Oštir, Krištof |
author_facet | Kanjir, Urška Greidanus, Harm Oštir, Krištof |
author_sort | Kanjir, Urška |
collection | PubMed |
description | • A review of 119 papers on ship detection and classification from optical satellite. • From 1978 to March 2017, showing an exponential growth in the number of papers. • Most published methods have very limited validation. • While big steps have been made, automatic algorithms are still far from perfect. • Increase in new observation and processing capabilities promises rapid advances. |
format | Online Article Text |
id | pubmed-5877374 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | American Elsevier Pub. Co |
record_format | MEDLINE/PubMed |
spelling | pubmed-58773742018-04-03 Vessel detection and classification from spaceborne optical images: A literature survey Kanjir, Urška Greidanus, Harm Oštir, Krištof Remote Sens Environ Article • A review of 119 papers on ship detection and classification from optical satellite. • From 1978 to March 2017, showing an exponential growth in the number of papers. • Most published methods have very limited validation. • While big steps have been made, automatic algorithms are still far from perfect. • Increase in new observation and processing capabilities promises rapid advances. American Elsevier Pub. Co 2018-03-15 /pmc/articles/PMC5877374/ /pubmed/29622842 http://dx.doi.org/10.1016/j.rse.2017.12.033 Text en © 2018 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Kanjir, Urška Greidanus, Harm Oštir, Krištof Vessel detection and classification from spaceborne optical images: A literature survey |
title | Vessel detection and classification from spaceborne optical images: A literature survey |
title_full | Vessel detection and classification from spaceborne optical images: A literature survey |
title_fullStr | Vessel detection and classification from spaceborne optical images: A literature survey |
title_full_unstemmed | Vessel detection and classification from spaceborne optical images: A literature survey |
title_short | Vessel detection and classification from spaceborne optical images: A literature survey |
title_sort | vessel detection and classification from spaceborne optical images: a literature survey |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5877374/ https://www.ncbi.nlm.nih.gov/pubmed/29622842 http://dx.doi.org/10.1016/j.rse.2017.12.033 |
work_keys_str_mv | AT kanjirurska vesseldetectionandclassificationfromspaceborneopticalimagesaliteraturesurvey AT greidanusharm vesseldetectionandclassificationfromspaceborneopticalimagesaliteraturesurvey AT ostirkristof vesseldetectionandclassificationfromspaceborneopticalimagesaliteraturesurvey |