Marc Ebner

58 papers receiving 969 citations

Peers

Marc Ebner
Comparison fields: 5 of 108
  • Computer Vision and Pattern Recognition 423
  • Atomic and Molecular Physics, and Optics 402
  • Cognitive Neuroscience 243
  • Media Technology 105
  • Artificial Intelligence 295
Replace Zhiyong Yang with:
Zhiyong Yang China
Ulrich Engelke Australia
Takahiko Horiuchi Japan
Claudio Cusano Italy
David R. Martin United States
Bernice E. Rogowitz United States
A. Ravishankar Rao United States
Leon D. Harmon United States
Th. Gevers Netherlands
Ian R. Moorhead United Kingdom
Marc Ebner relative to Zhiyong Yang China Zhiyong Yang's profile →
Citations per field
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Citations per year

Countries citing papers authored by Marc Ebner

Since Specialization
Citations

This map shows the geographic impact of Marc Ebner's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Marc Ebner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marc Ebner more than expected).

Fields of papers citing papers by Marc Ebner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marc Ebner. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Marc Ebner. The network helps show where Marc Ebner may publish in the future.

Co-authors

The 25 scholars most cited alongside Marc Ebner, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Marc Ebner Line = papers co-authored together Marc Ebner links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 61 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Color constancy
2007371
2 200168
3 200866
4 200653
5 201346
6 201346
7 200245
8 200242
9 200340
10 200922
11 201422
12 200622
13 201313
14
On The Use Of Negative Selection In An Artificial Immune System
200212
15 200712
16 200712
17 200311
18 200610
19 20029
20 20119

About Marc Ebner

Marc Ebner is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Atomic and Molecular Physics, and Optics, Cognitive Neuroscience and Social Psychology, having authored 61 papers that have together received 1.0k indexed citations. Recurring topics across this work include Color Science and Applications (18 papers), Image Enhancement Techniques (15 papers), Evolutionary Algorithms and Applications (13 papers), Color perception and design (8 papers), Visual perception and processing mechanisms (7 papers), Reinforcement Learning in Robotics (6 papers), Advanced Vision and Imaging (6 papers) and Evolution and Genetic Dynamics (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (423 citations), Atomic and Molecular Physics, and Optics (402 citations), Cognitive Neuroscience (243 citations), Media Technology (105 citations) and Artificial Intelligence (295 citations). Marc Ebner has collaborated with scholars based in Germany, United Kingdom and United States. Frequent co-authors include Mark Shackleton, Rob Shipman, Tom Schaul, Tommy Thompson, John Levine, Simon M. Lucas, Jörg Albert, Oguzhan Ulucan, Andreas Zell and Julian Togelius. Their work appears in journals such as Genetic Programming and Evolvable Machines, Future Generation Computer Systems, The Visual Computer, Robotics and Autonomous Systems and Computational Intelligence and Neuroscience.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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