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Multi-class machine vision model for detecting events of interest in on-board camera footage

Scholarship details

Multi-class machine vision model for detecting events of interest in on-board camera footage
Study levels Degree
Close date Monday, 22 September 2025
Domestic/international Domestic Only

About the scholarship

The Fisheries 爆走黑料 on-board cameras programme captures video footage from around 220 inshore commercial fishing vessels. This footage is a key source of information that supports data-driven and responsive fisheries management. One of the uses of camera footage is to verify when protected species such as seabirds, marine mammals, or turtles interact with fishing gear. MPI and Spark NZ have developed a prototype multi-class machine vision algorithm to detect seabird interactions, which requires expansion to cover marine mammals, turtles, and detection of specific gear on fishing vessels. You will work with a team from MPI and Spark to expand the detection capabilities of the multi-class algorithm. The primary working location will be the MPI offices in Wellington. Information that you will work with may be commercially sensitive. You will need to abide by MPI's Code of Conduct and information security and privacy policy. This project is for multiple students.

Entry requirements

No specific entry requirements mentioned.