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Initiative #64

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Automatic detection of unidentified fish sounds

Listed in the registry Pilot Original language : English

About the initiative

Description of the initiative

We used Random Forestes and Convolutional Neural Networks (CNN) algorithms trained on manually detected fish sounds to detect fish sounds collected on a passive acoustic monitoring project. The result is an easy-to-use, open-source software called FishSoundFinder, implemented with the CNN detector. Random Forests and CNN

AI family

Perception and Understanding

Bucket rationale

Interprets audio patterns from environmental input, which is an AI perception task.

Lifecycle

  1. Ideation

    Stage status : Completed

    May 29, 2025

  2. Assessment

    Stage status : Completed

  3. Approved

    Stage status : Completed

  4. Development

    Stage status : Completed

  5. Pilot

    Stage status : In progress

  6. Production

    Stage status : Upcoming

  7. Archived

    Stage status : Upcoming

Schedule for this initiative

  • Completed
  • In progress
  • Planned
  • Not applicable
  • Today
2025 May Jun Jul Aug Sep Oct Nov Dec 2026 Jan Feb Mar Apr May Jun Jul Aug Sep
  1. Ideation

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Contacts

Requester
Quan, Eric
Sector contact
Dana Haggarty / Xavier Mouy
Subject matter expert
Haggarty, Dana

Data and tools

Sector
Ecosystems and Oceans Science
Region
Pacific
Submitted on
May 29, 2025