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Understanding
Participants
Summary
We are interested in how to solve real world practical problems using computer vision with both classical algorithms and machine learning. Environmental monitoring is a particular focus of our work and we have developed a variety systems for image understanding for underwater image classification [1] and for fish monitoring [2]. As well as the applications we are interested in developing the underpinning theory [3].
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Partners
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Publications
[1] . Game and G.D. Finlayson. "Machine learning for non-experts: A more accessible and simpler approach to automatic benthic habitat classification", Ecological Informatics 81, 102619, 2024.
[2] G. French et al. "Deep neural networks for analysis of fisheries surveillance video and automated monitoring of fish discards",ICES Journal of Marine Science 77 (4), 1340-1353, 2020.
[3] G. French, M. Mackiewicz and M. Fisher. " Self-ensembling for visual domain adaptation", International Conference on Learning Representations, 2018.