His scientific interests lie mostly in Visualization, Topology, Flow visualization, Data visualization and Vector field. His Visualization study is concerned with the larger field of Artificial intelligence. Gerik Scheuermann interconnects Grid and Interpolation in the investigation of issues within Topology.
His work deals with themes such as Fluid dynamics, Streamlines, streaklines, and pathlines, Application domain and Computer graphics, which intersect with Flow visualization. His research on Data visualization frequently connects to adjacent areas such as Context. The concepts of his Vector field study are interwoven with issues in Discrete mathematics, Gravitational singularity, Singularity, Computational geometry and Data set.
His primary areas of study are Visualization, Vector field, Topology, Artificial intelligence and Data visualization. The Visualization study combines topics in areas such as Flow, Context, Computer graphics, Flow visualization and Data science. His Flow visualization research includes elements of Fluid dynamics, Streamlines, streaklines, and pathlines and Theoretical computer science.
His Vector field research incorporates themes from Generalization, Mathematical analysis, Pure mathematics, Rotation and Algorithm. His Topology study combines topics in areas such as Tensor field and Scalar. The various areas that Gerik Scheuermann examines in his Artificial intelligence study include Computer vision and Pattern recognition.
Visualization, Data science, Vector field, Information retrieval and Data visualization are his primary areas of study. His study in Visualization is interdisciplinary in nature, drawing from both Domain, Field, Scalar, Tensor field and Neuroscience. His work in Tensor field addresses issues such as Stress, which are connected to fields such as Tensor.
His Vector field research focuses on Applied mathematics and how it relates to Lyapunov exponent. His Information retrieval research is multidisciplinary, relying on both Literary criticism and Reading. He frequently studies issues relating to Visual analytics and Data visualization.
Gerik Scheuermann focuses on Visualization, Data visualization, Data science, Vector field and Algorithm. His Visualization study is associated with Artificial intelligence. His Data visualization research is multidisciplinary, incorporating perspectives in Visual analytics, Systems engineering, Structure and Lever.
His Data science research integrates issues from Scheme and Semantics. His research integrates issues of Segmentation, Mathematical analysis, Linear approximation, Pure mathematics and Scalar in his study of Vector field. His studies deal with areas such as Theoretical computer science, Independent set, Invariant, Flow visualization and Scaling as well as Algorithm.
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Data, Information, and Knowledge in Visualization
Min Chen;D. Ebert;H. Hagen;R.S. Laramee.
IEEE Computer Graphics and Applications (2009)
On Close and Distant Reading in Digital Humanities: A Survey and Future Challenges
Stefan Jänicke;Greta Franzini;Muhammad Faisal Cheema;Gerik Scheuermann.
Detection and visualization of closed streamlines in planar flows
T. Wischgoll;G. Scheuermann.
IEEE Transactions on Visualization and Computer Graphics (2001)
Clifford Fourier transform on vector fields
J. Ebling;G. Scheuermann.
IEEE Transactions on Visualization and Computer Graphics (2005)
Continuous topology simplification of planar vector fields
Xavier Tricoche;Gerik Scheuermann;Hans Hagen.
ieee visualization (2001)
A topology simplification method for 2D vector fields
Xavier Tricoche;Gerik Scheuermann;Hans Hagen.
ieee visualization (2000)
Visualizing nonlinear vector field topology
G. Scheuermann;H. Kruger;M. Menzel;A.P. Rockwood.
IEEE Transactions on Visualization and Computer Graphics (1998)
Topology Tracking for the Visualization of Time-Dependent Two-Dimensional Flows
Xavier Tricoche;Thomas Wischgoll;Gerik Scheuermann;Hans Hagen.
Computers & Graphics (2002)
Surface techniques for vortex visualization
Christoph Garth;Xavier Tricoche;Tobias Salzbrunn;Tom Bobach.
Multifield visualization using local statistical complexity
Heike Janicke;Alexander Wiebel;Gerik Scheuermann;Wolfgang Kollmann.
IEEE Transactions on Visualization and Computer Graphics (2007)
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