Machine learning applied to big data from marine cabled observatories: A case study of sablefish monitoring in the NE Pacific
Ideas for this paper resulted from discussions during the international workshop “Marine cabled observatories: moving towards applied monitoring for fisheries management, ecosystem function and biodiversity”, funded by Ocean Networks Canada and co-hosted by ICM-CSIC, in Barcelona, Spain on 4–5 October 2018.-- 15 pages, 8 figures, 1 table, supplementary material https://www.frontiersin.org/articles/10.3389/fmars.2022.842946/full#supplementary-material.-- Data availability statement: The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material. We made all training computations on the Google Colab notebook12. To repeat the training, please clone the Google Drive repository containing the annotated data at13. All detection, tracking, and time-series analyses are freely available for reproduction at
| Main Authors: | , , , , , |
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| Other Authors: | |
| Format: | artículo biblioteca |
| Language: | English |
| Published: |
Frontiers Media
2022-08
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| Subjects: | Big data, Machine learning, Marine observatories, Automated video analysis, Fishery independent monitoring, Ocean network Canada, Intelligent marine observing systems, Neural network, |
| Online Access: | http://hdl.handle.net/10261/280709 http://dx.doi.org/10.13039/501100011033 http://dx.doi.org/10.13039/501100000780 http://dx.doi.org/10.13039/501100001805 |
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