JellyMonitor: automated detection of jellyfish in sonar images using neural networks

Geoff French, Michal Mackiewicz, Mark Fisher, Mike Challis, Peter Knight, Brian Robinson, Angus Bloomfield

Research output: Chapter in Book/Report/Conference proceedingConference contribution

21 Citations (Scopus)
38 Downloads (Pure)


JellyMonitor is an self-contained automated system that detects jellyfish blooms and reports their presence. It uses an embedded platform to analyse sonar imagery captured by a sonar imaging device. The software utilises a combination of classic computer vision techniques and deep neural networks to detect and classify objects captured by the sonar imaging device. We report on the development of this system and present results obtained from deploying a prototype.
Original languageEnglish
Title of host publicationProceedings of the 14th IEEE International Conference on Signal Processing
PublisherThe Institute of Electrical and Electronics Engineers (IEEE)
ISBN (Electronic)978-1-5386-4673-1
Publication statusPublished - Aug 2018

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