Funded by the PML internal research program and the European Space Agency the innovative study – titled “Detection and Classification of Floating Plastic Litter Using a Vessel-Mounted Video Camera and Deep Learning” – was carried out as part of an undergraduate placement project, with the results now published in the journal Remote Sensing

The model was able to classify the presence or absence of plastic in an image with an accuracy of 95% and capable of differentiating different types of plastic – for example a plastic bag or bottle – with an accuracy of 68%.

It is now envisaged that the technique could be more widely applied using crewed or autonomous vessels, such as PML’s proposed long-range autonomous research vessel, the Oceanus, thereby revolutionising existing capabilities to monitor floating plastic litter.

Dr Victor Martinez Vicente, Senior Scientist at PML said:

“In situ harmonised and simplified observations of floating marine plastic debris are currently very limited in the literature. We have aimed to tackle the scarcity of these observations through our research on low-cost automated observations. We hope that this initial step will lead to an increase of in situ observations everywhere, but especially in poorer countries where marine litter is usually a great problem.

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