DOI · DOI-0225 · record R2538
Automated otolith aging using image processing [2024 INV#WO0000000109315]
Department of the Interior · USGS
Overview
- Development stage
- PilotSource: b) Pilot – The use case has been deployed in a limited test or pilot capacity.
- High-impact designation
- Not high-impactSource: c) Not high-impact
- Impact justification
- Not reported
- Start date
- 2023-10-01 (day precision)Source: 10/1/2023
- Withheld from public reporting
- NoSource: a) No
Mission
- Topic area
- Science
- Operational functions
- Image and video analysis Derived by keyword rules; see methodology
Problem the AI is intended to solve
Fisheries managers and researchers often need to know the age of fish for population estimates, stock assessment, and similar projects. Fish otoliths (an ear bone) often accumulated rings annual (similar to tress).
Expected benefits
automate this process to see if we can reduce variability across individual agers and automate the aging process of counting otolith rings possibly saving time
System outputs
automated aging process
Technology
- AI classification
- Classical / predictive MLSource: Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relatio…
- System name(s)
- Not reported
- Custom-developed code
- No
- Public source code
- Not reported
Sourcing
- How it was built
- Developed in-houseSource: b) Developed in-house
- Vendor (as reported)
- Not reported
- Vendors (standardized)
- None on the standard list
A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.
Data and privacy
- Involves PII
- No
- Privacy Impact Assessment
- Not reported
- Authorization to Operate
- No
- Demographic features
- k) None of the above
- Training and evaluation data
- Otolith images (pictures) with known ages
- Federal Data Catalog
- Not reported
Governance
0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.
Pre-deployment testingNo answer reported
AI impact assessmentNo answer reported
Independent reviewNo answer reported
Ongoing monitoringNo answer reported
Operator trainingNo answer reported
Fail-safeNo answer reported
Appeal processNo answer reported
User and public consultationNo answer reported
Potential impacts and how they were identified
Not reported