DOC · DOC-132 · record R2988
Integrating query learning and domain adaptation to develop robust ML algrithms to determine species and count using optical data gathered from fisheries dependent and fisheries independent data collected in the Gulf of Mexico.
Department of Commerce · NOAA
Overview
- Development stage
- Status not reported
- High-impact designation
- Not reported
- Impact justification
- Not reported
- Start date
- Not reported
- Withheld from public reporting
- Not reported
Mission
- Topic area
- Not reported
- Operational functions
- No function tag matched Derived by keyword rules; see methodology
Problem the AI is intended to solve
Not reported
Expected benefits
Not reported
System outputs
Not reported
Technology
- AI classification
- Not reported
- System name(s)
- Not reported
- Custom-developed code
- Not reported
- Public source code
- Not reported
Sourcing
- How it was built
- Not reported
- 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
- Not reported
- Privacy Impact Assessment
- Not reported
- Authorization to Operate
- Not reported
- Demographic features
- Not reported
- Training and evaluation data
- Not reported
- 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