SUPR
A system for automated analysis of subsea movies using citizen science and machine learning
Dnr:

NAISS 2023/22-1359

Type:

NAISS Small Compute

Principal Investigator:

Matthias Obst

Affiliation:

Göteborgs universitet

Start Date:

2024-01-01

End Date:

2025-01-01

Primary Classification:

10611: Ecology

Allocation

Abstract

This project has developed a data system to analyse large amounts of subsea movie data for marine ecological research. The data system consists of three distinct modules for data management and archiving, citizen science, and machine learning (ML) in a high performance computation environment. For the latter we now want to establish a reliable and potentially long-term HPC instance at SNIC. A full description of the project is avaialble here https://preprints.arphahub.com/article/60597/. This project is part of the Vinnova financed Ocean Data Factory (https://oceandatafactory.se/) and the resulting services will become part of the Swedish Biodiversity Data Infrastructure (biodiversitydata.se/).