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.
|Title of host publication||Proceedings of the 14th IEEE International Conference on Signal Processing|
|Publisher||The Institute of Electrical and Electronics Engineers (IEEE)|
|Publication status||Published - Aug 2018|