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Summer Term 2004





Image Analysis and Image Understanding (2 Lectures + 2 Exercises, Kurth / Mangoldt)
Lectures: Thursday, 13:45-15:15, EH 214
Exercises: Thursday, 07:30-09:00, EH 214

Keywords: Perception and cognitive psychology; point operations, folding, local window operations, morphological operations, Fourier transformation, wavelets; segmentation procedures, matching, classification; knowledge representation for image understanding; neural networks; analysis of stereo images, analysis of frame sequences.

Foundations of Data Mining (2 Lectures, Kurth)
Wednesday, 09:15-10:45, EH 214

Under "Data Mining" we subsume methods for the automatic recognition of patterns in large collections of data (e.g. data bases of complete enterprises, sensor data, network transfer data). For these methods, foundations from statistics, algebra and learning theory will be provided. Keywords: Construction of decision trees, Bayes classification, association rules, concept lattices, linear models, data cubes, learing paradigms, PAC model, Occam's razor, learing from noisy examples, online learning.

Foundations of Digital Printing (1 Lecture + 1 Exercise, Mangoldt / Kurth)
Tuesday, 15:30-17:00, EH 214

Development trends and structures in the print media industry; fonts, techniques for preparation for printing, colour spaces, colour management; reproduction technique; software in the preparation for printing; scan process, digital cameras, workflow systems; CD and DVD technique, data archiving; printing methods; cost calculation; supplementary processing techniques.

Pattern recognition in images and 3D data (2 SE, Kurth / Mangoldt)
Tuesday, 17:30-19:00, EH 214

Selected, recent texts about image segmentation and methods of 3D data evaluation with applications in the virtual reconstruction of scenes will be read and discussed. A focus will lie on the utilization of prior knowledge about the expected objects in a scene during object identification and classification.

Data analysis and visualization in bioinformatics (2 PR, Kurth / Buck-Sorlin / Kniemeyer)
Wednesday, 17:30-19:00, EH 214

After an intensive short course concerning foundations of bioinformatics the participants will have the opportunity to work at typical tasks of analysis and visualization in small, competently supervises projects: Pattern matching in DNA sequences, visualization of protein structures, modelling morphology and genetics of an agrarian crop plant with graph grammmars, fractal dimension analysis, and other topics for choice.

 

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Last Modifications: October 11, 2004