Initiative #118
Use of artificial intelligence models to facilitate seafloor video annotations in conservation areas.
Listed in the registry Pilot Original language : English
About the initiative
Description of the initiative
The purpose of this initiative is to utilize AI to facilitate seafloor video annotations collected as part of the MCT and Benthic Ecology programs in the NL Region. A large number of vidEcosystems and Oceans Science is collected annually, and manual video annotation (e.g., locating and counting observations) is extremely time-consuming. A published “object detection model” (FathomNet Megalodon Detector, YOLOv8x) trained using marine taxa by MBARI is currently being used to identify objects in our seafloor images. The model does not identify the objects (e.g., to species), but it largely accelerates the process given that locating objects is the most time-consuming part of the work.
AI family
- AI sub-category
- Computer Vision
- AI capability
- Species Identification and Biological Annotation
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Same AI sub-category (Computer Vision): they could share a solution.
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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