Polyp activity estimation and monitoring for cold water corals with a deep learning approach
Osterloff J, Nilssen I, Järnegren J, Buhl-Mortensen P, Nattkemper TW. Polyp activity estimation and monitoring for cold water corals with a deep learning approach. In: Proceedigs of CVAUI 2016 (ICPR Workshop) . 2016. Fixed underwater observatories (FUOs) equipped with a variety of sensors including...
Published in: | 2016 ICPR 2nd Workshop on Computer Vision for Analysis of Underwater Imagery (CVAUI) |
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ftubbiepub:oai:pub.uni-bielefeld.de:2906522 2023-05-15T17:08:18+02:00 Polyp activity estimation and monitoring for cold water corals with a deep learning approach Osterloff, Jonas Nilssen, Ingunn Järnegren, Johanna Buhl-Mortensen, Pål Nattkemper, Tim Wilhelm 2016 https://pub.uni-bielefeld.de/record/2906522 eng eng info:eu-repo/semantics/altIdentifier/doi/10.1109/CVAUI.2016.013 https://pub.uni-bielefeld.de/record/2906522 info:eu-repo/semantics/closedAccess http://purl.org/coar/resource_type/c_5794 info:eu-repo/semantics/conferenceObject doc-type:conferenceObject text 2016 ftubbiepub https://doi.org/10.1109/CVAUI.2016.013 2022-02-08T22:35:54Z Osterloff J, Nilssen I, Järnegren J, Buhl-Mortensen P, Nattkemper TW. Polyp activity estimation and monitoring for cold water corals with a deep learning approach. In: Proceedigs of CVAUI 2016 (ICPR Workshop) . 2016. Fixed underwater observatories (FUOs) equipped with a variety of sensors including cameras, allow long-term monitoring with a high temporal resolution of a limited area of interest. FUOs equipped with HD cameras enable in situ monitoring of biological activity, such as live cold-water corals on a level of detail down to individual polyps. We present a workflow which allows monitoring the activity of cold water coral polyps automatically from photos recorded at the FUO LoVe (Lofoten - Vesterålen). The workflow consists of three steps: First the manual polyp activity-level identification, carried out by three observers on a region of interest in 13 images to generate a gold standard. Second, the training of a convolutional neural network (CNN) on the gold standard to automate the polyp activity classification. Third, the computational activity classification is integrated into an algorithmic estimation of polyp activity in a region of interest. We present results obtained for an image series from April to November 2015 that shows interesting temporal behavior patterns correlating with other posterior measurements. Conference Object Lofoten Vesterålen PUB - Publications at Bielefeld University Lofoten Vesterålen ENVELOPE(14.939,14.939,68.754,68.754) 2016 ICPR 2nd Workshop on Computer Vision for Analysis of Underwater Imagery (CVAUI) 1 6 |
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PUB - Publications at Bielefeld University |
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ftubbiepub |
language |
English |
description |
Osterloff J, Nilssen I, Järnegren J, Buhl-Mortensen P, Nattkemper TW. Polyp activity estimation and monitoring for cold water corals with a deep learning approach. In: Proceedigs of CVAUI 2016 (ICPR Workshop) . 2016. Fixed underwater observatories (FUOs) equipped with a variety of sensors including cameras, allow long-term monitoring with a high temporal resolution of a limited area of interest. FUOs equipped with HD cameras enable in situ monitoring of biological activity, such as live cold-water corals on a level of detail down to individual polyps. We present a workflow which allows monitoring the activity of cold water coral polyps automatically from photos recorded at the FUO LoVe (Lofoten - Vesterålen). The workflow consists of three steps: First the manual polyp activity-level identification, carried out by three observers on a region of interest in 13 images to generate a gold standard. Second, the training of a convolutional neural network (CNN) on the gold standard to automate the polyp activity classification. Third, the computational activity classification is integrated into an algorithmic estimation of polyp activity in a region of interest. We present results obtained for an image series from April to November 2015 that shows interesting temporal behavior patterns correlating with other posterior measurements. |
format |
Conference Object |
author |
Osterloff, Jonas Nilssen, Ingunn Järnegren, Johanna Buhl-Mortensen, Pål Nattkemper, Tim Wilhelm |
spellingShingle |
Osterloff, Jonas Nilssen, Ingunn Järnegren, Johanna Buhl-Mortensen, Pål Nattkemper, Tim Wilhelm Polyp activity estimation and monitoring for cold water corals with a deep learning approach |
author_facet |
Osterloff, Jonas Nilssen, Ingunn Järnegren, Johanna Buhl-Mortensen, Pål Nattkemper, Tim Wilhelm |
author_sort |
Osterloff, Jonas |
title |
Polyp activity estimation and monitoring for cold water corals with a deep learning approach |
title_short |
Polyp activity estimation and monitoring for cold water corals with a deep learning approach |
title_full |
Polyp activity estimation and monitoring for cold water corals with a deep learning approach |
title_fullStr |
Polyp activity estimation and monitoring for cold water corals with a deep learning approach |
title_full_unstemmed |
Polyp activity estimation and monitoring for cold water corals with a deep learning approach |
title_sort |
polyp activity estimation and monitoring for cold water corals with a deep learning approach |
publishDate |
2016 |
url |
https://pub.uni-bielefeld.de/record/2906522 |
long_lat |
ENVELOPE(14.939,14.939,68.754,68.754) |
geographic |
Lofoten Vesterålen |
geographic_facet |
Lofoten Vesterålen |
genre |
Lofoten Vesterålen |
genre_facet |
Lofoten Vesterålen |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.1109/CVAUI.2016.013 https://pub.uni-bielefeld.de/record/2906522 |
op_rights |
info:eu-repo/semantics/closedAccess |
op_doi |
https://doi.org/10.1109/CVAUI.2016.013 |
container_title |
2016 ICPR 2nd Workshop on Computer Vision for Analysis of Underwater Imagery (CVAUI) |
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1 |
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6 |
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1766064025154617344 |