Abigail Clennell

Masters Student
School of Engineering and Computer Science

address
CO322, Cotton Building, Kelburn Campus

Thesis Info

Research Interests: Computer Vision, Deep Learning, Facial Recognition, Wildlife Conservation
Thesis Title: AI-Driven Kākā Facial Recognition for Conservation
Supervisor: Dr Andrew Lensen, Dr Rachael Shaw

Publications

Neu(t)ralMC: energy-efficient open source Monte Carlo algorithm for assessing photon transport in turbid media
An open source energy efficient hybrid Monte Carlo and machine learning algorithm for assessing light transport in turbid scattering media

Main.GraduateForm edit

ResearchAreas	Computer Vision, Deep Learning, Facial Recognition, Wildlife Conservation
ThesisTitle	AI-Driven Kākā Facial Recognition for Conservation
Supervisor	Dr Andrew Lensen, Dr Rachael Shaw
Qualifications	BSc in Computer Science with an AI specialisation, Computer Graphics, and a Minor in Maths. BSc Hons First Class in Computer Graphics
Photo

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Topic revision: 15 Apr 2024, clenneabig