Automatic detection, identification and counting of deep-water snappers on underwater baited video using deep learning

Automatic detection, identification and counting of deep-water snappers on underwater baited video using deep learning

Deep-sea demersal fisheries in the Pacific have strong commercial, cultural, and recreational value, especially snappers (Lutjanidae) which make the bulk of catches. Yet, managing these fisheries is challenging due to the scarcity of data. Stereo-Baited Remote Underwater Video Stations (BRUVS) can p...

Full description

Saved in:
Bibliographic Details
Main Authors: Florian Baletaud, Sébastien Villon, Antoine Gilbert, Jean-Marie Côme, Sylvie Fiat, Corina Iovan, Laurent Vigliola
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-02-01
Series:Frontiers in Marine Science
Subjects:
deep-water snapper fisheries
artificial intelligence
semi-automatic
BRUVS
faster R-CNN
Online Access:https://www.frontiersin.org/articles/10.3389/fmars.2025.1476616/full
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items