Mr Ioannis Maniadis Metaxas
Artificial Intelligence (Undergraduate)
The module introduces the student to techniques used in Artificial Intelligence including problem formulation, search, logic, probability and decision theory. The module aims to provide the participants with a basic knowledge of artificial intelligence; an understanding of how to design an intelligent agent; and knowledge of basic AI tools.
Machine Learning (Postgraduate)
The aim of the module is to give students an understanding of machine learning methods, including pattern recognition, clustering and neural networks, and to allow them to apply such methods in a range of areas.
Machine Learning for Visual Data Analysis (Postgraduate/Undergraduate)
The module will cover the following topics: The Discrete Fourier Transform and the frequency content of images. The design and use of Gabor filters. Principal Component Analysis for denoising and compression. Unsupervised classification via feature space clustering. Texture segmentation with Gabor filters.