His main research concerns Visualization, Algorithm, Geometry, Computer graphics and Data visualization. Data mining covers Bernd Hamann research in Visualization. His Algorithm research includes themes of Discrete mathematics, Interpolation, Subdivision surface, Grid and Tetrahedron.
His Geometry research is multidisciplinary, incorporating perspectives in Curve fitting and Spline. His Data visualization study combines topics from a wide range of disciplines, such as Interactive visualization and Segmentation. His work focuses on many connections between Creative visualization and other disciplines, such as Data analysis, that overlap with his field of interest in Gene expression, Computational biology and Gene.
His primary scientific interests are in Visualization, Computer graphics, Algorithm, Artificial intelligence and Computer vision. While the research belongs to areas of Visualization, Bernd Hamann spends his time largely on the problem of Data science, intersecting his research to questions surrounding Data management. His studies in Computer graphics integrate themes in fields like Interactive visualization, Grid and Octree.
His Algorithm research includes themes of Mathematical optimization, Vector field, Surface and Wavelet. The subject of his Surface research is within the realm of Geometry. His works in Segmentation and Image segmentation are all subjects of inquiry into Artificial intelligence.
His primary areas of investigation include Visualization, Artificial intelligence, Computer vision, Data visualization and Algorithm. His Visualization research incorporates elements of Theoretical computer science, Computer-integrated manufacturing, Human–computer interaction and Topology. As part of one scientific family, Bernd Hamann deals mainly with the area of Theoretical computer science, narrowing it down to issues related to the Scalability, and often Process.
Bernd Hamann has included themes like Machine learning and Reverse engineering in his Artificial intelligence study. His Data visualization study incorporates themes from Visual analytics and Information visualization. His work on Metric expands to the thematically related Algorithm.
Visualization, Artificial intelligence, Computer vision, Data visualization and Theoretical computer science are his primary areas of study. His studies deal with areas such as Supercomputer, Manufacturing engineering, Computer-integrated manufacturing, Graph and Topology as well as Visualization. His study in the fields of Computational topology under the domain of Topology overlaps with other disciplines such as Probability distribution.
His research in Artificial intelligence intersects with topics in Functional magnetic resonance imaging and Neuroinformatics. His study in the field of Segmentation, Voxel and Object detection is also linked to topics like Object-class detection and Improved method. The various areas that Bernd Hamann examines in his Data visualization study include IBM, Information visualization and Grid network.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
The asymptotic decider: resolving the ambiguity in marching cubes
Gregory M. Nielson;Bernd Hamann.
ieee visualization (1991)
A data reduction scheme for triangulated surfaces
Computer Aided Geometric Design (1994)
D.F. Wiley;N. Amenta;D.A. Alcantara;D. Ghosh.
ieee visualization (2005)
A Quantitative Spatiotemporal Atlas of Gene Expression in the Drosophila Blastoderm
Charless C. Fowlkes;Cris L. Luengo Hendriks;Cris L. Luengo Hendriks;Soile V.E. Keränen;Soile V.E. Keränen;Gunther H. Weber;Gunther H. Weber.
Curvature approximation for triangulated surfaces
Geometric modelling (1993)
A topological hierarchy for functions on triangulated surfaces
P.-T. Bremer;B. Hamann;H. Edelsbrunner;V. Pascucci.
IEEE Transactions on Visualization and Computer Graphics (2004)
Multiresolution techniques for interactive texture-based volume visualization
Eric LaMar;Bernd Hamann;Kenneth I. Joy.
ieee visualization (1999)
A Practical Approach to Morse-Smale Complex Computation: Scalability and Generality
A. Gyulassy;P.-T. Bremer;B. Hamann;V. Pascucci.
IEEE Transactions on Visualization and Computer Graphics (2008)
FastBit: interactively searching massive data
K. Wu;S. Ahern;E. W. Bethel;E. W. Bethel;J. Chen.
Lawrence Berkeley National Laboratory (2009)
Topology-Controlled Volume Rendering
G.H. Weber;S.E. Dillard;H. Carr;V. Pascucci.
IEEE Transactions on Visualization and Computer Graphics (2007)
Profile was last updated on December 6th, 2021.
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