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Conference object . 2022
License: CC BY
Data sources: Datacite
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ZENODO
Conference object . 2022
License: CC BY
Data sources: Datacite
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Other literature type . 2022
License: CC BY
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Marine ecosystem monitoring: a new deep learning application for reef mapping based on a citizen science framework

descriptionPublicationkeyboard_double_arrow_right Conference object , Other literature type 30 Sep 2022Publisher:Zenodo
Authors: Talpaert Justine; Contini Matteo; Bonhommeau Sylvain; Barde Julien; Chevrier Thomas; Joly Alexis;

doi: 10.5281/zenodo.7129735 , 10.5281/zenodo.7129736

Marine ecosystem monitoring: a new deep learning application for reef mapping based on a citizen science framework

Abstract

Poster created for the symposium of WIOMSA 2022 (Western Indian Ocean Marine Science Association). It depicts the collaboration between Seatizen project (Ifremer) and G2OI project (IRD) to automate the production of marine species distribution maps using citizen science for data acquisition and deep learning for species recognition.

Keywords

participative science, species recognition, marine ecology, Deep learning, computer vision

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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