Oscar Bryan

Machine Learning for the Detection of Unexploded Ordnance Using Synthetic Aperture Sonar

Project Summary

My research area is the application of machine learning methods for the detection of sea disposed, unexploded ordnance. Advances in underwater sensing technologies (synthetic aperture Sonar) and autonomous vehicles has resulted in large amounts of survey data at a high (cm) resolution. This development motivates the development of autonomous mapping and assessment for the remediation of historic weapons dumped at sea.

Awards

Doctoral Recognition Award Winner 2021

Research Interests

Sonar, deep learning, Bayesian machine learning and explainable AI.

Background

MEng Mechanical Engineering at University of Bath, ART-AI MRes

Supervisors

Dr Alan Hunter

Dr Tom Fincham Haines