Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
year round Details This research is aimed at developing scalable Bayesian approaches able to solve complex and high dimensional problems with multiple objects and multi-sensor data. One such problem is
-
which videos can be with low resolution and low quality. Based on the video data coming sequentially in real time the most common problems of interest are: automatic detection of moving objects, followed
-
Bayesian system identification in nonlinear engineering dynamics
-
modelling and analytical skills in building and testing an acoustic monitoring tool to detect hidden defects in sewer pipes as a part of the EU multi-institutional project AI:LINERS. The work will be carried
-
of rail with wider city and regional transport networks. A focus of this work is the application of optimisation techniques (e.g. evolutionary algorithms, or Bayesian techniques) to identify high performing
-
Human Grip of Hand-Held Objects School of Mechanical, Aerospace and Civil Engineering PhD Research Project Self Funded Prof M Carre, Prof R Lewis Application Deadline: Applications accepted all
-
environments and inaccurate prior maps, to name a few. In order to cope with these challenges different methods will be developed. Knowledge of Bayesian methods for sensor data fusion, mapping and multiple
-
resulting impedance measured over a range of frequencies - has previously been applied for detecting cervical pre-cancers. We aim to adapt the EIS for use in oral tissues, specifically to identify potentially
-
these observations is that biases in the perceptual systems used by animals (including humans) to detect and process sensory information have played an important role in shaping communication signal evolution. In
-
chatbots in other chronic conditions (e.g., Type 1 Diabetes Mellitus), this PhD project aims to develop the first developmentally appropriate chatbot for YP with IBD. Objectives: To gather the views of YP