Beom-Su Seo

420 citations
22 papers · 248 · h-index 8

Impact in

Papers in

Beom-Su Seo

21 papers receiving 231 citations

Peers

Beom-Su Seo
Comparison fields: 5 of 51
  • Computational Mathematics 9
  • Computer Vision and Pattern Recognition 123
  • Control and Systems Engineering 106
  • Computer Networks and Communications 57
  • Artificial Intelligence 68
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Jeff Hyams United States
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Citations per year

Countries citing papers authored by Beom-Su Seo

Since Specialization
Citations

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

Fields of papers citing papers by Beom-Su Seo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Beom-Su Seo. 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 Beom-Su Seo. The network helps show where Beom-Su Seo may publish in the future.

Co-authors

The 13 scholars most cited alongside Beom-Su Seo, 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 Beom-Su Seo Line = papers co-authored together Beom-Su Seo links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200880
2 200650
3
The PEIS kernel : a middleware for ubiquitous robotics
200728
4 201912
5 201511
6
The PEIS-Ecology Project: a progress report
200710
7 20078
8 20168
9 20187
10 20147
11
Steps toward an ecology of physically embedded intelligent systems
20065
12 20185
13 20194
14
Using JavaSpace for a PEIS ecology
20062
15 20242
16 20042
17 20122
18 20221
19
Integrating Robots into Smart Environments
20061
20 20241

About Beom-Su Seo

Beom-Su Seo is a scholar working on Computer Vision and Pattern Recognition, Mechanical Engineering, Control and Systems Engineering, Computer Networks and Communications and Artificial Intelligence, having authored 22 papers that have together received 248 indexed citations. Recurring topics across this work include Modular Robots and Swarm Intelligence (8 papers), Context-Aware Activity Recognition Systems (7 papers), Robotics and Automated Systems (7 papers), Autonomous Vehicle Technology and Safety (3 papers), Advanced Neural Network Applications (3 papers), Face and Expression Recognition (2 papers), Robotics and Sensor-Based Localization (2 papers) and Geomagnetism and Paleomagnetism Studies (2 papers). The work is most often cited by research in Computational Mathematics (9 citations), Computer Vision and Pattern Recognition (123 citations), Control and Systems Engineering (106 citations), Computer Networks and Communications (57 citations) and Artificial Intelligence (68 citations). Beom-Su Seo has collaborated with scholars based in South Korea, Sweden and Germany. Frequent co-authors include Mathias Broxvall, Alessandro Saffiotti, Seung‐Ik Lee, Jin Ha Lee, Marcella Astrid, Young-Jo Cho, Byungjae Park, Muhammad Zaigham Zaheer, Sung Hoon Kim and Juyong Park. Their work appears in journals such as Sensors, Han-guk marin enjinieoring hakoeji and 2018 20th International Conference on Advanced Communication Technology (ICACT).

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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