RootPainter models and outputs for Mycale lingua within image data from the Lofoten Vesterålen Ocean Observatory (2017-19) and an ROV survey of the Tisler Reef (2021)

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Main Authors: Clark, Hannah Poppy, Smith, Abraham G, McKay Fletcher, Daniel, Larsson, Ann I, Jaspars, Marcel, De Clippele, Laurence Helene
Format: Dataset Open Access
Language:en
Published: PANGAEA 2024
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author Clark, Hannah Poppy
Smith, Abraham G
McKay Fletcher, Daniel
Larsson, Ann I
Jaspars, Marcel
De Clippele, Laurence Helene
author_facet Clark, Hannah Poppy
Smith, Abraham G
McKay Fletcher, Daniel
Larsson, Ann I
Jaspars, Marcel
De Clippele, Laurence Helene
collection Datos científicos de ciencias marinas y ambientales
contents Five models were developed using RootPainter; four to detect and predict the surface area of the deep-sea sponge Mycale lingua and one to identify laser scales. Three of the sponge models were trained and applied to time-lapse images collected by the Lofoten Vesterålen Ocean Observatory. The fourth sponge model and laser model were developed and used on extracted video frames from an ROV survey of the Tisler reef. The total observatory dataset contained 18,346 images, consisting of 9,173 images each of the Mycale lingua sponges 'Magnus' and 'Mini' from 2017-2019. The total ROV video frame dataset contained 1,420 images from the East of the reef, captured in 2021.
format Dataset Open Access
id pangaea_https___doi_org_10_1594_PANGAEA_966298
institution PANGAEA
language en
publishDate 2024
publisher PANGAEA
record_format pangaea
spellingShingle RootPainter models and outputs for Mycale lingua within image data from the Lofoten Vesterålen Ocean Observatory (2017-19) and an ROV survey of the Tisler Reef (2021)
Clark, Hannah Poppy
Smith, Abraham G
McKay Fletcher, Daniel
Larsson, Ann I
Jaspars, Marcel
De Clippele, Laurence Helene
automated species detection; Binary Object; Binary Object (File Size); Binary Object (Media Type); File content; iAtlantic; Integrated Assessment of Atlantic Marine Ecosystems in Space and Time; interactive machine learning; Lofoten_Vesterålen_Ocean_Observatory; Lofoten/Vesterålen; marine image analysis; Model, Rootpainter; Mycale lingua; Remote operated vehicle; RootPainter; ROV; sponge surface area; Tisler_Reef_Video_Survey; Tisler Reef, Skagerrak
Five models were developed using RootPainter; four to detect and predict the surface area of the deep-sea sponge Mycale lingua and one to identify laser scales. Three of the sponge models were trained and applied to time-lapse images collected by the Lofoten Vesterålen Ocean Observatory. The fourth sponge model and laser model were developed and used on extracted video frames from an ROV survey of the Tisler reef. The total observatory dataset contained 18,346 images, consisting of 9,173 images each of the Mycale lingua sponges 'Magnus' and 'Mini' from 2017-2019. The total ROV video frame dataset contained 1,420 images from the East of the reef, captured in 2021.
title RootPainter models and outputs for Mycale lingua within image data from the Lofoten Vesterålen Ocean Observatory (2017-19) and an ROV survey of the Tisler Reef (2021)
topic automated species detection; Binary Object; Binary Object (File Size); Binary Object (Media Type); File content; iAtlantic; Integrated Assessment of Atlantic Marine Ecosystems in Space and Time; interactive machine learning; Lofoten_Vesterålen_Ocean_Observatory; Lofoten/Vesterålen; marine image analysis; Model, Rootpainter; Mycale lingua; Remote operated vehicle; RootPainter; ROV; sponge surface area; Tisler_Reef_Video_Survey; Tisler Reef, Skagerrak
url https://doi.org/10.1594/PANGAEA.966298