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Tracking fish abundance by underwater image recognition

Author
Marini, S.; Fanelli, E.; Sbragaglia, V.; Azurro, E.; Del Rio, J.; Aguzzi, J.
Type of activity
Journal article
Journal
Scientific reports
Date of publication
2018-09-13
Volume
8
Number
Article number: 13748
First page
1
Last page
12
DOI
https://doi.org/10.1038/s41598-018-32089-8 Open in new window
Project funding
FP7-312463-FixO3 Fixed Point Open Ocean Observatories Network
Repository
http://hdl.handle.net/2117/121281 Open in new window
URL
https://www.nature.com/articles/s41598-018-32089-8 Open in new window
Abstract
Marine cabled video-observatories allow the non-destructive sampling of species at frequencies and durations that have never been attained before. Nevertheless, the lack of appropriate methods to automatically process video imagery limits this technology for the purposes of ecosystem monitoring. Automation is a prerequisite to deal with the huge quantities of video footage captured by cameras, which can then transform these devices into true autonomous sensors. In this study, we have developed a...
Citation
Marini, S., Fanelli, E., Sbragaglia, V., Azurro, E., Del Rio, J., Aguzzi, J. Tracking fish abundance by underwater image recognition. "Scientific reports", 13 Setembre 2018, vol. 8, núm. Article number: 13748, p. 1-12.
Keywords
Cabled video-observatories, Ecosystem monitoring
Group of research
SARTI - Technological Development Center for Remote Acquisition and Data Processing System
SARTI-MAR -

Participants

  • Marini, Simone  (author)
  • Fanelli, Emanuela  (author)
  • Sbragaglia, Valerio  (author)
  • Azurro, Ernesto  (author)
  • Del Rio Fernandez, Joaquin  (author)
  • Aguzzi, Jacopo  (author)

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