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Deep learning for detection and counting of Nephrops norvegicus from underwater videos

ICES Journal of Marine Science, ISSN: 1095-9289, Vol: 81, Issue: 7, Page: 1307-1324
2024
  • 0
    Citations
  • 0
    Usage
  • 4
    Captures
  • 1
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

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  • Captures
    4
  • Mentions
    1
    • News Mentions
      1
      • 1

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Data on Marine Science Reported by Researchers at University of the Balearic Islands (Deep Learning for Detection and Counting of Nephrops Norvegicus From Underwater Videos)

2024 AUG 15 (NewsRx) -- By a News Reporter-Staff News Editor at NewsRx Science Daily -- Data detailed on Life Sciences - Marine Science have

Article Description

The Norway lobster (Nephrops norvegicus) is one of the most important fishery items for the EU blue economy. This paper describes a software architecture based on neural networks, designed to identify the presence of N. norvegicus and estimate the number of its individuals per square meter (i.e. stock density) in deep-sea (350–380 m depth) Fishery No-Take Zones of the northwestern Mediterranean. Inferencing models were obtained by training open-source networks with images obtained from frames partitioning of in submarine vehicle videos. Animal detections were also tracked in successive frames of video sequences to avoid biases in individual recounting, offering significant success and precision in detection and density estimations.

Bibliographic Details

Antoni Burguera Burguera; Francisco Bonin-Font; Damianos Chatzievangelou; Maria Vigo Fernandez; Jacopo Aguzzi; Cigdem Beyan

Oxford University Press (OUP)

Earth and Planetary Sciences; Agricultural and Biological Sciences; Environmental Science

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