IA-2026-0113
Develop a deep-learning model to age capelin otoliths: application for stock assessment
Pilot Ecosystems and Oceans Science
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
Strategic alignment
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Contacts
- Subject matter expert
- Winegardner, Amanda
Lifecycle
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Ideation
Stage status : Completed
August 28, 2026 August 28, 2026
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Assessment
Stage status : Not applicable
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Approved
Stage status : Not applicable
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Development
Stage status : Not applicable
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Pilot
Stage status : In progress
August 28, 2026
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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
Change log (12 entries)
Public history of this initiative's key events. The team's internal exchanges are not shown.
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