Initiative #64
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
- AI sub-category
- Audio Event Detection
- AI capability
- Species Identification and Biological Annotation
Similar initiatives
Same AI sub-category (Audio Event Detection): they could share a solution.
- 164 Development of an abundance index for an under surveyed capelin stock · Ecosystems and Oceans Science
- 163 Recherches sur l’Intelligence artificielle pour le traitement automatisé des données d’acoustiques sous-marine · Ecosystems and Oceans Science
- 145 Automatic detection of unidentified fish sounds · Ecosystems and Oceans Science
Lifecycle
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Ideation
Stage status : Completed
May 29, 2025
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Assessment
Stage status : Completed
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Approved
Stage status : Completed
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Development
Stage status : Completed
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Pilot
Stage status : In progress
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Production
Stage status : Upcoming
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Archived
Stage status : Upcoming
Schedule for this initiative
- Completed
- In progress
- Planned
- Not applicable
- Today
- Ideation
A similar need?
Nobody has come forward yet. If your team faces the same problem, say so: it helps bring initiatives together and share a solution.
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