Initiative #121
Develop a deep-learning model to age capelin otoliths: application for stock assessment
Listed in the registry Pilot Original language : English
About the initiative
Description of the initiative
Investigate the utility of applying a deep-learning model developed by the DFO Gulf Region for aging fish otoliths; specifically, to determine the age of capelin in the 2J3KL stock in Newfoundland for use in stock assessments. Otolith aging is currently done visually using a microscope, this proposed method would automate that process to save time and resources, while reducing human error and bias
AI family
Automation and Decision Support
- AI capability
- Species Identification and Biological Annotation
Bucket rationale
Applies AI for prediction, decision-making, or automation of rule-based tasks.
Lifecycle
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Ideation
Stage status : Completed
June 1, 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
- Smith, Melannie
- Sector contact
- Smith, Melannie
- Subject matter expert
- Winegardner, Amanda
- Smith, Melannie
Data and tools
- Sector
- Ecosystems and Oceans Science
- Region
- National Capital Region
- Submitted on
- June 1, 2025