Beom Kwon

33 papers receiving 332 citations

Peers

Beom Kwon
Comparison fields: 5 of 52
  • Computer Vision and Pattern Recognition 142
  • Human-Computer Interaction 32
  • Computer Networks and Communications 84
  • Electrical and Electronic Engineering 159
  • Artificial Intelligence 76
Replace Mohd Fikri Azli Abdullah with:
Mohd Fikri Azli Abdullah Malaysia
Edwin Naroska Germany
Marco Bassoli Italy
Wanru Xu China
Akshay Nambi India
A. Sivasangari India
Dirk Reichardt Germany
Seon-Woo Lee South Korea
Biying Fu Germany
Lukas Köping Germany
Beom Kwon relative to Mohd Fikri Azli Abdullah Malaysia Mohd Fikri Azli Abdullah's profile →
Citations per field
00.5×3.2×
Mohd Fikri Azli Abdullah · 1×
Citations per year

Countries citing papers authored by Beom Kwon

Since Specialization
Citations

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

Fields of papers citing papers by Beom Kwon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 18 scholars most cited alongside Beom Kwon, 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 Kwon Line = papers co-authored together Beom Kwon links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201476
2 201740
3 201619
4 202117
5 202215
6 201614
7 201613
8 201712
9 201710
10 202010
11 20249
12 20209
13 20149
14 20208
15 20198
16 20188
17 20178
18 20238
19 20177
20 20157

About Beom Kwon

Beom Kwon is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Computer Networks and Communications, Artificial Intelligence and Control and Systems Engineering, having authored 38 papers that have together received 367 indexed citations. Recurring topics across this work include Human Pose and Action Recognition (6 papers), PAPR reduction in OFDM (5 papers), Wireless Communication Networks Research (5 papers), Algorithms and Data Compression (5 papers), Advanced MIMO Systems Optimization (4 papers), Cooperative Communication and Network Coding (4 papers), Hand Gesture Recognition Systems (3 papers) and Gait Recognition and Analysis (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (142 citations), Human-Computer Interaction (32 citations), Computer Networks and Communications (84 citations), Electrical and Electronic Engineering (159 citations) and Artificial Intelligence (76 citations). Beom Kwon has collaborated with scholars based in South Korea, United States and China. Frequent co-authors include Sanghoon Lee, Seonghyun Kim, Junghwan Kim, Taewan Kim, Ho-Jae Lee, Sangjoon Park, H. C. Song, Hyukmin Son, Jinwoo Kim and Jiwoo Kang. Their work appears in journals such as IEEE Access, IEEE Transactions on Broadcasting, Applied Sciences, IEEE Transactions on Vehicular Technology and Wireless 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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