Human-in-the-loop artificial intelligence for identification of fish behavior with high-frequency periodic acoustic fish tags

Innovasea produces fish tags and receivers to track the presence and motion of fish and marine mammals while underwater. Fish tracking (acoustic telemetry) is used by researchers worldwide to determine the abundance and habits of marine life, make decisions about fishing seasons and allowed catches, and help protect marine mammals. Innovasea has developed a novel high-frequency tag technology that is suitable for very small fish and generates more precise trajectories. However, the new smaller fish tags send no explicit identification information so signals from a specific fish tag are isolated from background noise and other fish tags based on the period and/or pattern of the signals. To obtain useful fish tracking trajectories, Innovasea currently applies machine learning models that work in many environments but need to be retrained for other environments.

In this project we will apply advanced deep learning techniques to large manually processed training sets provided by Innovasea to eliminate the manual preprocessing steps.

Faculty Supervisor:

Christopher Whidden

Student:

Partner:

InnovaSea Marine Systems Canada Inc

Discipline:

Computer science

Sector:

Information and cultural industries; Manufacturing

University:

Dalhousie University

Program: