Daniel Kersten

7.5k citations
143 papers · 5.3k · h-index 39

Impact in

Papers in

Daniel Kersten

137 papers receiving 5.0k citations

Peers

Daniel Kersten
Comparison fields: 5 of 131
  • Cognitive Neuroscience 4.2k
  • Experimental and Cognitive Psychology 749
  • Computer Vision and Pattern Recognition 1.1k
  • Computer Graphics and Computer-Aided Design 185
  • Social Psychology 820
Replace David C. Knill with:
David C. Knill United States
Jacob Beck United States
V. S. Ramachandran United States
R. von der Heydt United States
Manish Singh United States
Pascal Mamassian France
James T. Todd United States
Tom Trościanko United Kingdom
Frederick A. A. Kingdom Canada
Ennio Mingolla United States
Daniel Kersten relative to David C. Knill United States David C. Knill's profile →
Citations per field
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David C. Knill · 1×
Citations per year

Countries citing papers authored by Daniel Kersten

Since Specialization
Citations

This map shows the geographic impact of Daniel Kersten'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 Daniel Kersten with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Kersten more than expected).

Fields of papers citing papers by Daniel Kersten

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Kersten. 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 Daniel Kersten. The network helps show where Daniel Kersten may publish in the future.

Co-authors

The 25 scholars most cited alongside Daniel Kersten, 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 Daniel Kersten Line = papers co-authored together Daniel Kersten links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 143 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2002382
2 2006325
3 1987253
4 1999245
5 2003243
6 1991177
7 1998164
8 2005150
9 1997143
10 2008139
11 1995139
12 1995132
13 2004123
14 1998110
15 2008108
16 1987105
17 200397
18 201195
19 198379
20 198479

About Daniel Kersten

Daniel Kersten is a scholar working on Cognitive Neuroscience, Computer Vision and Pattern Recognition, Atomic and Molecular Physics, and Optics, Social Psychology and Computer Graphics and Computer-Aided Design, having authored 143 papers that have together received 5.3k indexed citations. Recurring topics across this work include Visual perception and processing mechanisms (93 papers), Neural dynamics and brain function (35 papers), Color Science and Applications (26 papers), Face Recognition and Perception (23 papers), Visual Attention and Saliency Detection (20 papers), Advanced Vision and Imaging (17 papers), Color perception and design (13 papers) and Tactile and Sensory Interactions (7 papers). The work is most often cited by research in Cognitive Neuroscience (4.2k citations), Experimental and Cognitive Psychology (749 citations), Computer Vision and Pattern Recognition (1.1k citations), Computer Graphics and Computer-Aided Design (185 citations) and Social Psychology (820 citations). Daniel Kersten has collaborated with scholars based in United States, Germany and Türkiye. Frequent co-authors include Scott O. Murray, David C. Knill, Gordon E. Legge, Paul Schrater, Hüseyin Boyacı, Pascal Mamassian, Alan Yuille, Fang Fang, Michael J. Tarr and Arthur E. Burgess. Their work appears in journals such as Journal of Vision, Vision Research, Perception, Journal of the Optical Society of America A and Current Biology.

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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