This thesis poses the underwater image analysis as challenging computer vision problems and aims to address those using deep learning techniques. It proposes state-of-the-art deep learning methods to automatically classify coral reefs and kelp forests. It also extends these methods to automatically depict the trends of changing coral population and coverage of kelp forests. Lastly, the thesis proposes to generate synthetic parts data for automatic detection of lobsters in the complex underwater background, a challenging task in the marine research community.
|Qualification||Doctor of Philosophy|
|Award date||25 Mar 2019|
|Publication status||Unpublished - 2019|