EE4305-Fuzzy-Neural-Systems-for-Intelligent-Robotics

This module introduces fuzzy logic and neural networks, two tools used in robotics, and their application. It examines the principles of fuzzy sets and fuzzy logic, which leads to fuzzy inference and control. It also covers the structures and learning process of a neural network including genetic algorithm and classification. Topics covered include: fuzzy set theory, fuzzy systems and control of robots, basic concepts of neural networks, single-layer and multilayer perceptions, self-organizing maps, neural network training and neural network modelling of robots. Applications to Robotics will be specifically elaborated throughout the course.

EE4212-Computer-Vision

The goal of this module is to introduce the students to the problems and solutions of modern computer vision, with the main emphasis on recovering properties of the 3D world from image and video sequence. After this module, students are expected to be able to understand and compute the basic geometric and photometric properties of the 3D world (such as point depth and surface orientation), and to apply various methods for video manipulation such as segmentation, matting, and composition. Main topics covered include: Singular value decomposition, projective geometry, Marr's paradigm, calibration problems, correspondence and flow, epipolar geometry, motion estimation, reflectance models, shape from shading, photometric stereo, color processing, texture analysis and synthesis, advanced segmentation, matting and composition techniques.

EE4704-Image-Processing-and-Analysis

The goal of this module is to introduce students to the fundamental concepts underlying digital image processing and techniques for manipulating and analysing image data. This course will provide students with a good foundation in computer vision and image processing, which is important for those intending to proceed to biomedical engineering, intelligent systems and multimedia signal processing. The following topics are taught: elements of a vision system, image acquisition, 2-D discrete Fourier transform, image enhancement techniques, theoretical basis and techniques for image compression, segmentation methods including edge detection, feature extraction including texture measurement, and object recognition.