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Intelligent Data Engineering and Automated Learning Laboratory
(L. W. Chan, K. H. Wong, I. King and K. S. Leung)
The Intelligent Data Engineering and Automated Learning Laboratory focuses on automated learning methodologies and applies them to data mining, pattern recognition, multimedia database etc. It investigates mainly the following topics:
Computer Vision, Image Processing Pattern Recognition:
One focus is to use neural networks to perform image compression,
face recognition and animation, as well as multimedia databases
(Chan, King). The other focus is binocular visual fusion with neural networks. We have applied the condensation technique for the tracking (Wong). The fourth one is to use concatenated neural networks for geometric invariant object recognition (Chan).
Financial Data Mining:
Data Mining techniques are applied to financial data, in order to extract the hidden information and knowledge. Decision supporting systems and portfolio management systems are designed based on the knowledge. (Chan)
Genetic Algorithms and Programming:
Research and applications of parallel genetic algorithms and Genetic Parallel Programming (GPP) on multiprocessors and FPGA are investigated. Another research project is on the evolution of novel Neural, Bayesian and Nonlinear Integral Networks. The theory and
application of adaptive evolutionary algorithms are being investigated (Leung, Lee).
Speech and Music Signal Processing:
One focus is to use neural network approaches to develop
systems for speaker identification and speech recognition
of isolated words and continuous speech in Cantonese
(Chan). Another focus is on the analysis of music signal for automatic transcription and lyric insertion. (Wong). The
third focus is on the detection and error correction of
sentences structure using recurrent neural networks (Chan).
Temporal Information Processing and Signal Processing:
One feature is to use mixture models, unsupervised/supervised
learning and recurrent networks for modelling and prediction
of non-stationary time series with financial applications
(Chan).
Multimedia Image Databases:
This project is to design and implement a content-based image
retrieval engine to access graphical images easily using colour,
texture, shape, sketch, and text with advanced database indexing
methods, statistical techniques, image processing procedures, and neural networks (King, Fu, Chan).
DNA Microarray Data Analysis:
Data mining techniques are designed and applied to the analysis and visualization of the gene expression data. (Chan)
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