Maria Petrou

Professor of Image Analysis
School of Electronics Computing and Mathematics
University of Surrey
Guildford, GU2 7XH, United Kingdom
http://www.ee.surrey.ac.uk/Personal/M.Petrou

Title: 3D texture analysis for medical applications

Abstract:
Volume data are very common in Medicine. However, they are difficult to visualise, yet alone to assess properties like volumetric isotropy or variation. Currently clinicians see such data slice by slice, they do not and they cannot take advantage of the full information conveyed by such data. This talk will present a way of assessing the texture of 3D volume data, a way of visualising such information, and some applications of the approach to schizophrenia and Alzheimer's desease.


José C. Príncipe

BellSouth Professor and Director
Computational NeuroEngineering Laboratory
EB 451, Bldg #33
University of Florida
Gainesville, FL 32611
http://www.cnel.ufl.edu/principe/principe.html

Title: Information Theoretic Learning: A Nonparametric Approach

Abstract:
This talk will present a new cost function for adaptation based on Renyi's entropy. In order to obtain a practical nonparametric cost function for supervised or unsupervised training of linear or nonlinear mappers, we integrate Renyi's definition with a Parzen estimator. This estimator of entropy does not require a data model, and resembles an interaction model for learning (the information potential).

Properties of the information potential will be presented, and several learning algorithms (batch, stochastic gradient, and a recursive entropy estimator) will be derived. Results in feature extraction, unsupervised clustering, blind source separation and information fitlering will be presented.


Paulo J. S. G. Ferreira

Dep. de Electrónica e Telecomunicações
Universidade de Aveiro
3810-193 Aveiro, Portugal
http://www.ieeta.pt/~pjf

Title: Handling impulsive noise

Abstract:
Dealing with impulsive noise remains a challenge, despite the efforts of many people and the existence of several distinct approaches. This talk addresses the issue of impulsive noise removal. A few of the possible approaches will be considered, giving some attention to the two basic frameworks that must be faced when discussing the problem: the analog case, and the digital case. The techniques discussed are nonlinear, and under certain conditions lead to the total removal of the noise. The connections between the techniques discussed and other approaches (including error control coding) are also discussed.