Publikationsdatum:
2024-05-06
Beschreibung:
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.
Schlagwort(e):
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
Materialart:
Dataset
Format:
text/tab-separated-values, 8 data points