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Event(s) on November 2010
- Thursday, 4th November, 2010
Title: CMIV DL: Image Processing and Computational Intelligence Methods for Computer-assisted Skin Cancer Diagnosis Speaker: Prof. Maciej J. Ogorzalek, Jagiellonian University Krakow, Poland Time/Place: 17:00 - 18:00 (Preceded by Tea Reception at 4:30 pm)
RRS905, Sir Run Run Shaw Building, HSH Campus, Hong Kong Baptist University
Abstract: Digital photography provides powerful tools for computer-assisted diagnosis systems in dermatology. Dermoscopy is a special photography technique which enable taking photos of skin lesions in chosen lighting conditions. Computer-assisted techniques and image processing methods are used for feature extraction and pattern recognition in the selected images. Special techniques used in skin-image processing are discussed in detail. Feature extraction and classification techniques based on statistical learning and model ensembling techniques provide very powerful tools which can assist the doctors in taking decisions. Performance of classifiers will be discussed in specific case of melanoma cancer diagnosis. The techniques have been tested on a large data set of images.
- Monday, 22nd November, 2010
Title: Efficient Numerical Methods for Stochastic Maxwell Equations and Applications in Spectrometer Design Speaker: Prof. ZHOU Haomin, School of Mathematics, Georgia Institute of Technology, USA Time/Place: 11:00 - 12:00
FSC1217, Fong Shu Chuen Library, HSH Campus, Hong Kong Baptist University
Abstract: In this presentation, we present a stochastic model for general spatially incoherent sources with applications in photonic crystal. The model naturally incorporates the incoherent property and leads to stochastic Maxwell equations. We also propose a fast numerical method based on Wiener Chaos Expansions (WCE), which convert the random equations into coupled system of deterministic equations, so that they can be solved using efficient deterministic methods. In the applications of photonic crystal, the new methods can achieve 2 order of magnitude faster computation time over the standard method.