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CIRG - Research  -  Neural Networks 



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OVERVIEW

The focus of the neural networks group is to investigate aspects of training and optimization of neural networks, and to apply neural networks to solve real-world problems. The activities of this focus area are mainly centered around architecture selection, active learning, and the development of new an efficient training algorithms. Some work is done on self-organizing maps.

Current applications are directed towards data mining, spam detection, user authentication, fraud detection, gesture recognition, and trading on financial markets. Applications of self-organization maps to exploratory data analysis, data mining, and species identification are done.

ACTIVE MEMBERS

List the current members actively doing research in this focus area. [ Show ]

ALUMNI MEMBERS

S van der Stockt

M.Sc Completed in 2008

E Dean

M.Sc Started in 2002

J Pun

M.Sc Completed

E Clements

Hons-B.Sc Completed in 2003

U Paquet

M.Sc Completed in 2003

R van den Hoven

Hons-B.Sc Completed in 2003

A Ismail

PhD Started in 2005
M.Sc Completed in 2001

A Adejumo

M.Sc Completed in 1999

GROUP PUBLICATIONS

List publications of this research focus area. [ Show ]

MEMBER PROFILE



 Name:

 James Chi-Him Pun

Portrait photo

 E-mail:

 jamesp@davaisoft.co.za

 Group(s):

 Image Analysis
 Neural Networks

 

 Degree specific information: M.Sc

 Title:

 Gesture Recognition with Application in Music Arrangement

 Abstract:

This thesis studies the interaction with music synthesis systems using hand gestures. Traditionally users of such systems were limited to input devices such as buttons, pedals, faders, and joysticks. The use of gestures allows the user to interact with the system in a more intuitive way. Without the constrain of input devices, the user can simultaneously control more elements within the music composition, thus increase the level of the system's responsiveness to the musician's creative thoughts. A working system of this concept is implemented, employing computer vision and machine intelligence techniques to recognise the user's gestures.

 Supervisor / Co-Supervisor:

 AP Engelbrecht
 F vd Bergh

 Thesis:

 Not available for download yet.




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