The report descibes the results of the AI master project at the University of Maastricht. It covers the development of the language to describe Entity Relational Bayesian Networks (ERBN) and the tools to use this language.
Authors: P. Hanckmann, M. v.d. Heijden, P. Mertens, S. Uyttendaele
The research was based on tools that can process documents (diaries) and place them in a document space. This high dimensional document space had to be reduced to a three dimensional space and projected on a sphere. With all the documents represented on a sphere it should be possible to see clusters of documents, zoom in on them and to see more detail.
Authors: M. de Mulder, C. Porteners, L. Ramekers, P. Hanckmann, P. Mertens
The research was based on automated speaker recognition in single and multi speaker environments. All software was written in MatLab. And the research was based on different recognition systems (Gaussian Mixture Model, Neural Networks and Nearest Neighbours while using cc, mfcc and lpc as methods to extract the coefficients). The research questions where: ...
Authors: D. Bloembergen, ing. P. Hanckmann, A. Lautenbach, B. Mehlkop, F. Schadd
Here you can find the abstract of our final report.
The KneeTwister is a device which will be used to measure the laxity in the knee joint. It also measures the angle between the upper and lower leg during an internal and external rotation.
Authors: ing. P. Hanckmann , ing. E. Mulders
|
|
38.107.191.101 www.hanckmann.net for more information. © 2006 Patrick Hanckmann; All rights reserved. |