Teaching Computers How to See Rocks - Using Computer Vision Models to Extract Visual Datasets

Abstract:
The mining industry is currently going through a significant phase of digital transformation to try and meet the rising global demand for minerals. As part of this digitalisation and modernisation, mining companies are collecting larger volumes of more complex data than ever before. Technologies that can assist in turning data into information and insights are key to prevent geoscientists from drowning in their new sea of data.
In this talk, we will explore how recent advances in computer vision - specifically in the field of deep learning - have provided algorithms and workflows that have the ability to efficiently augment and automate the many observational tasks in geoscience such as drill core logging. Several case studies will be presented to demonstrate how these models are trained and deployed to solve challenging geoscience problems.
Brenton Crawford:
Brenton Crawford is a geologist, data scientist, entrepreneur and mining technology enthusiast. He studied geology and geophysics at Monash University and began his career in consulting working for PGN Geoscience in a number of geological and geophysical roles in both exploration and mining. Brenton has also worked as a geophysicist and data scientist for MMG Exploration working in nickel, copper and zinc exploration and project generation in Australia, Africa and South America.
In 2015, Brenton co-founded Solve Geosolutions - Australia’s first exploration and mining focused data science consultancy which has since been acquired. In 2018, Brenton co-founded Datarock - a computer vision technology company geared at building productionised image and video analysis solutions for exploration and mining where he has served as both its Head of Business Development and Chief Operating Officer. Brenton currently serves as Datarock‘s Chief Geoscientist and Technologist.