Machine learning classification of Canadian mammal bones

Natural history collections and the specimens stored within are vital to our understanding of biodiversity, ecology, and evolution. To both preserve and increase their accessibility, efforts are being made to digitize the world’s natural history collections. In herbariums (natural history collections for plants), machine learning is being used to assist the digitization process by classifying unlabelled specimens. In this project, we will use machine learning to classify Canadian mammal skulls and mandibles. Additionally, we will use machine learning to help resolve issues of taxonomy in groups such as wolves, lemmings/voles, and deer mice. This project will serve as a case study for machine learning classification of mammal bones as well as a possible precursor to a citizen science machine learning application.

Faculty Supervisor:

Katie Marshall

Student:

Partner:

Canadian Museum of Nature

Discipline:

Life Sciences

Sector:

Life Sciences (not health); Artificial Intelligence; Environmental Science and Technology

University:

The University of British Columbia

Program: