Thomas Zöller

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Most cost function based clustering or partitioning methods measure the compactness of groups of data. In contrast to this picture of a point source in feature space, some data sources are spread out on a low-dimensional manifold which is embedded in a high dimensional data space. This property is adequately captured by the criterion of connectedness which(More)
Pairwise data clustering is a well founded grouping technique based on relational data of objects which has a widespread application domain. However, its applicability suflers from the disadvantageous fact that N objects give rise to N ( N 1)/2 relations. To cure this unfavorable scaling, techniques to sparsely sample the relations have been developed. Yet(More)
Unsupervised Image Segmentation is one of the central issues in Computer Vision. From the viewpoint of exploratory data analysis, segmentation can be formulated as a clustering problem in which pixels or small image patches are grouped together based on local feature information. In this contribution, parametrical distributional clustering (PDC) is(More)
In this contribution we analyze communication requirements of multi-agent simulation systems using IT-SimBw -- developed at Fraunhofer IAIS -- as an example. A focus is put on issues concerning inter-agent communication but complementary aspects of user interaction and coupling with C2 systems are also discussed. We propose an augmented version of the(More)
Automated segmentation of images has been considered an important intermediate processing task to extract semantic meaning from pixels. We propose an integrated approach for image segmentation based on a generative clustering model combined with coarse shape information and robust parameter estimation. The sensitivity of segmentation solutions to image(More)
Unsupervised image segmentation can be formulated as a clustering problem in which pixels or small image patches are grouped together based on local feature information. In this contribution, parametric distributional clustering (PDC) is presented as a novel approach to image segmentation based on color and texture clues. The objective function of the PDC(More)
The aim of this paper is the presentation of the military multi-agent simulation system ITSimBw. Its decisive features include a strictly agent-based approach to modeling, in which every entity in a simulated environment can potentially become an active element. Technologically, ITSimBw is based on the <i>Flip-Tick-Architecture</i>. Moreover, a focus on IT(More)
The syntheses and molecular structures of the intramolecularly coordinated tin(II) compounds {CH(2)N(Me)CH(Me)CH(Ph)O}(2)SnL (2, L = lone pair; 4, L = W(CO)(5); 5, L = Cr(CO)(5)) and of the related hydroxido-substituted tin(IV) compound [{CH(2)N(Me)CH(Me)CH(Ph)O}(2)Sn(OH)](2)O, 6a, are reported. Also reported are the molecular structures of the enantiopure(More)
The automated segmentation of images into semantically meaningful parts requires shape information since lowlevel feature analysis alone often fails to reach this goal. We introduce a novel method of shape constrained image segmentation which is based on mixtures of feature distributions for color and texture as well as probabilistic shape knowledge. The(More)
The synthesis, radiolabeling and in vitro evaluation of new silicon-fluoride acceptor (SiFA) derivatized D(2)-receptor ligands is reported. The SiFA-technology simplifies the introduction of fluorine-18 into target specific biomolecules for Positron-Emission-Tomography (PET). However, one of the remaining challenges, especially for small molecules such as(More)