Is the use of deep learning an appropriate means to locate debris in the ocean without harming aquatic wildlife?

Zoe Moorton*, Zeyneb Kurt, Wai Lok Woo

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

With the global issue of marine debris ever expanding, it is imperative that the technology industry steps in. The aim is to find if deep learning can successfully distinguish between marine life and synthetic debris underwater. This study assesses whether we could safely clean up our oceans with Artificial Intelligence without disrupting the delicate balance of aquatic ecosystems.
Our research compares a simple convolutional neural network with a VGG-16 model using an original database of 1,644 underwater images and a binary classification to sort synthetic material from aquatic life. Our results show first insights to safely distinguishing between debris and life.
Original languageEnglish
Article number113853
Pages (from-to)1-7
Number of pages7
JournalMarine Pollution Bulletin
Volume181
Early online date1 Jul 2022
DOIs
Publication statusPublished - 1 Aug 2022

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