Demo Data from EDBT 2026 / reviewers in the wild / expert
Georges Abou Jaoudé
dblp:53/10628
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2012
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
1 paper |
Visualization and visual analytics · 100% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Bioinformatics and computational biology · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Visualization and visual analytics
biomedical visualization |
0.1 | 1 | 2012 | A Neuron Membrane Mesh Representation for Visualization of Electrophysiological Simulations · IEEE Trans. Vis. Comput. Graph. 2012 |
Bioinformatics and computational biology › computational neuroscience › computational electrophysiology
electrophysiological simulation |
0.0 | 1 | 2012 | A Neuron Membrane Mesh Representation for Visualization of Electrophysiological Simulations · IEEE Trans. Vis. Comput. Graph. 2012 |
Bioinformatics and computational biology
neuroscience |
0.0 | 1 | 2012 | A Neuron Membrane Mesh Representation for Visualization of Electrophysiological Simulations · IEEE Trans. Vis. Comput. Graph. 2012 |
Methods — techniques the papers use, named apart from their topics
morphological reconstruction · 0.3mesh generation · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2012 | A Neuron Membrane Mesh Representation for Visualization of Electrophysiological SimulationsabstractWe present a process to automatically generate three-dimensional mesh representations of the complex, arborized cell membrane surface of cortical neurons (the principal information processing cells of the brain) from nonuniform morphological measurements. Starting from manually sampled morphological points (3D points and diameters) from neurons in a brain slice preparation, we construct a polygonal mesh representation that realistically represents the continuous membrane surface, closely matching the original experimental data. A mapping between the original morphological points and the newly generated mesh enables simulations of electrophysiolgical activity to be visualized on this new membrane representation. We compare the new mesh representation with the state of the art and present a series of use cases and applications of this technique to visualize simulations of single neurons and networks of multiple neurons. Sebastien Lasserre, Juan Hernando, Sean L. Hill, Felix Schürmann, Pedro de Miguel Anasagasti, Georges Abou Jaoudé, Henry Markram |
IEEE Trans. Vis. Comput. Graph. | 6 |