Stewart, Ian

Project Title

Use of AI and vision techniques to quantify bycatch of fish, benthos and endangered, threatened and protected species in scallop fisheries


At present there is little published information on the bycatches associated with scallop dredge fisheries.  The limited published work to date (Szostek et al. 2016) has revealed considerable geographic variation in the composition and quantity of bycatch within the English Channel and Irish Sea scallop fisheries.

The PhD project aims to inform sustainable management of scallop fisheries and to support Project UK Fishery Improvement Projects by answering the following questions:

To what extent does the species composition of bycatch and amount caught vary from one unit of assessment to another?

To what extent does bycatch identification and quantity vary with season?

What is the minimum amount of sampling required to monitor bycatch?

The project will develop an automated system to acquire video data and 3D laser-scanning data during the catch-sorting process onboard fishing vessels, and will apply deep learning techniques to identify, quantify and size bycatch species.


HWU: Prof Michel Kaiser, Dr Marta Vallejo

Ulster: Dr Chris McGonigle

Aberystwyth: Prof Bernie Tiddeman

Bangor: Dr Natalie Hold


University Email: