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Machine-supported mineralogical interpretations from hyperspectral and geochemical datasets

posted on 28.07.2022, 23:38 authored by ANGELA AFONSO RODRIGUES

Geologists face the challenge of analysing large volumes of complex, multivariate and uncertain datasets. This contribution focusses on the creation of machine supported workflows for the analysis of multivariate datasets in order to identify mineralogy, and to support geologists to objectively analyse these datasets.


Campus location


Principal supervisor

Laurent Ailleres

Additional supervisor 1

Robin Armit

Additional supervisor 2

Lachlan Grose

Additional supervisor 3

Mehrtash Harandi

Year of Award


Department, School or Centre

Earth, Atmosphere and Environment

Additional supervisor 4

Matthew Cracknell


Doctor of Philosophy


Faculty of Science