Semantic Identification of objects of interest using Convoluted Neural Networks

Applications are invited for a self-funded, 3 year full-time or 6 year part-time PhD project.

The PhD will be based in the School of Computing and will be supervised by Dr Ioannis Kagalidis.

Neural Networks have proven to be effective in image recognition tasks. The ability to extract semantic information from near real time images is still somewhat not fully explored and still remains relatively elusive.  Humans are able to recognise objects and their path through space in real time. Consider cars that wait at a red traffic light. Humans are able to pick one and follow it through to the next traffic light. For a standard AI system, any car is the same as the next.  Semantic identification will almost certainly become a necessity in applications coping with the need to understand concepts as abstract as “follow that yellow car” and “has the accident completely blocked the motorway?” which would provide a high level of interaction between humans and AI systems. The School of Computing in the University of Portsmouth has an established and ongoing collaboration with the PCC and private stakeholders to investigate the application of Neural Networks in better traffic managements and generation of traffic flow models. 

Fees and funding

Visit the research subject area page for fees and funding information for this project.

Funding availability: Self-funded PhD students only. 

PhD full-time and part-time courses are eligible for the UK Government Doctoral Loan (UK and EU students only).

Bench fees

Some PhD projects may include additional fees – known as bench fees – for equipment and other consumables, and these will be added to your standard tuition fee. Speak to the supervisory team during your interview about any additional fees you may have to pay. Please note, bench fees are not eligible for discounts and are non-refundable.