Linkage Projects - Grant ID: LP220200949

Funding Activity

Website
http://dataportal.arc.gov.au/NCGP/Web/Grant/Grant/LP220200949

Funding Status
Active

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Funded Activity Summary

Self-supervised feature learning for rapid processing of marine imagery. Fast and reliable quantitative estimates of marine environmental health are needed for scientific studies, design and management of protected areas, and regulatory compliance of industrial activity in the ocean. Australia is collecting seafloor images at increasing rates but expert annotations are not keeping up, meaning that typical machine learning approaches struggle. This project will develop self-supervised techniques that use large amounts of unlabeled data to enhance performance. Our design takes advantage of additional information available for marine imagery such as geolocation and remote sensing context. We will explore how these representations can guide additional sampling and improve performance in classification tasks.

Funded Activity Details

Start Date: 01-07-2023

End Date: 30-06-2026

Funding Scheme: Linkage Projects

Funding Amount: $478,994.00

Funder: Australian Research Council

Research Topics

ANZSRC Field of Research (FoR)

Machine learning | Semi- and unsupervised learning | Field robotics |

ANZSRC Socio-Economic Objective (SEO)

Other Keywords

Assessment and Management of Benthic Marine Ecosystems | Field robotics | Machine learning | Robotics | Semi- and unsupervised learning

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