National Machine Learning Service
Exploreabout National Machine Learning Service
Marine imagery and annotation data on fish and shark assemblages provide powerful biodiversity reporting and impactful science communication.
The Australian Baited Remote Underwater Video (BRUV) Synthesis data asset (established through GlobalArchive) has the potential to contribute the type of data used to illustrate climate change impacts, reveal environmental change within marine parks and indicate pathways to maximise bio-economic management globally, however more data is needed.
The project will provide transformational data analytics and environmental reporting workflows. It will achieve this by:
Researchers, research organisations and government agencies will benefit from:
Our partners for this project are:
This project will ensure the future growth of the Australian BRUV synthesis data asset. This data asset has been identified as a critical component for the sustained monitoring of federal, state and territory marine park or reserve networks, where stereo-BRUVs are a key tool for the non-destructive monitoring of fish assemblages across a range of water depths.