Yoonsuck Choe

1.8k citations
108 papers · 924 · h-index 14

Impact in

    • Neural dynamics and brain function
    • Visual perception and processing mechanisms
    • EEG and Brain-Computer Interfaces
  • Biophysics top 5%
    • Cell Image Analysis Techniques

Papers in

Yoonsuck Choe

97 papers receiving 859 citations

Peers

Yoonsuck Choe
Comparison fields: 5 of 111
  • Cognitive Neuroscience 468
  • Biophysics 89
  • Artificial Intelligence 306
  • Cellular and Molecular Neuroscience 143
  • Computer Vision and Pattern Recognition 122
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Citations per year

Countries citing papers authored by Yoonsuck Choe

Since Specialization
Citations

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

Fields of papers citing papers by Yoonsuck Choe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 108 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005141
2 2015123
3 201350
4 199836
5 201929
6 201127
7 200919
8 200418
9 200717
10 201416
11 201116
12 201915
13
Directed Exploration in Reinforcement Learning with Transferred Knowledge
201214
14 200914
15 200413
16
Perceptual groupings in a self-organizing map of spiking neurons
200113
17 200813
18 200812
19 202012
20
Self-Organization and Segmentation with Laterally Connected Spiking Neurons
199710

About Yoonsuck Choe

Yoonsuck Choe is a scholar working on Cognitive Neuroscience, Artificial Intelligence, Computer Vision and Pattern Recognition, Biophysics and Cellular and Molecular Neuroscience, having authored 108 papers that have together received 924 indexed citations. Recurring topics across this work include Neural dynamics and brain function (48 papers), Visual perception and processing mechanisms (20 papers), Neural Networks and Applications (18 papers), Cell Image Analysis Techniques (17 papers), Action Observation and Synchronization (12 papers), Advanced Memory and Neural Computing (11 papers), Reinforcement Learning in Robotics (9 papers) and Advanced Fluorescence Microscopy Techniques (9 papers). The work is most often cited by research in Cognitive Neuroscience (468 citations), Biophysics (89 citations), Artificial Intelligence (306 citations), Cellular and Molecular Neuroscience (143 citations) and Computer Vision and Pattern Recognition (122 citations). Yoonsuck Choe has collaborated with scholars based in United States, South Korea and Germany. Frequent co-authors include Risto Miikkulainen, James A. Bednar, Joseph Sirosh, Jaerock Kwon, Yong Zhang, Yingyezhe Jin, Peng Li, Heejin Lim, Huei‐Fang Yang and John Keyser. Their work appears in journals such as Neurocomputing, Neural Computation, BMC Neuroscience, Biological Cybernetics and Neural Networks.

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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