Learning-based Resilient Image Compression for Object Detection

The project:

The PhD project is a collaborative project between MBDA UK and the University of Bristol’s Visual Information Laboratory, on ‘Learning-based Resilient Image Compression for Object Detection’.

The project comprises of two work areas:

• AI –based error resilience for image compression, and
• End-to-end optimized coding and detection framework.

The former part of the project seeks to improve the reconstruction quality of foreground objects that are within identified regions of interest. The latter focuses on developing an end-end optimized coding and detection framework. Developed solutions will be tailored to meet challenging scenarios (for example dealing with low resolution images and low transmission bitrates).

How to apply:

• All candidates should submit a full CV and covering letter to Dr Aaron Zhang ([email protected]).
• A Selection Panel will be established to review all applications and to conduct interviews of short-listed candidates.
• The selected candidate then submits their formal application for PhD at http://www.bris.ac.uk/pg-howtoapply (select PhD in Computer Science on the Programme Choice page and mention MBDA UK in the Funding and Research Details sections).

Candidate requirements: 

Applicants must hold/achieve a minimum of a merit at master’s degree level (or international equivalent) in a science, mathematics or engineering discipline. Applicants without a master’s qualification may be considered on an exceptional basis, provided they hold a first-class undergraduate degree. Please note, acceptance will also depend on evidence of readiness to pursue a research degree.

Essential: Excellent analytical skills and experimental acumen

Desirable: A background understanding in one or more of the following:

• Image and video Processing
• Artificial intelligence/Machine learning/Deep learning

Contacts:

For questions about the research topic, please contact Dr Aaron Zhang ([email protected]).

For questions about eligibility and the application process please contact Engineering Postgraduate Research Admissions [email protected]