Using unmanned aerial vehicles and machine learning to improve sea cucumber density estimation in shallow habitats Article

Kilfoil, James P, Rodriguez-Pinto, Ivan, Kiszka, Jeremy J et al. (2020). Using unmanned aerial vehicles and machine learning to improve sea cucumber density estimation in shallow habitats . ICES JOURNAL OF MARINE SCIENCE, 77(7-8), 2882-2889. 10.1093/icesjms/fsaa161

Open Access International Collaboration

cited authors

  • Kilfoil, James P; Rodriguez-Pinto, Ivan; Kiszka, Jeremy J; Heithaus, Michael R; Zhang, Yuying; Roa, Camilo C; Ailloud, Lisa E; Campbell, Matthew D; Wirsing, Aaron J

sustainable development goals

authors

publication date

  • December 1, 2020

published in

keywords

  • ABUNDANCE
  • CORAL-REEF
  • DEPOSIT-FEEDING HOLOTHURIANS
  • Fisheries
  • Holothuroidea
  • Life Sciences & Biomedicine
  • Marine & Freshwater Biology
  • Oceanography
  • PATTERN
  • Physical Sciences
  • Science & Technology
  • abundance estimation
  • convolution neural network
  • drone
  • fisheries-independent surveys
  • invertebrates
  • visual surveys

Digital Object Identifier (DOI)

publisher

  • OXFORD UNIV PRESS

start page

  • 2882

end page

  • 2889

volume

  • 77

issue

  • 7-8