Hyun Kwon

1.0k citations
77 papers · 744 · h-index 17

Impact in

Papers in

Hyun Kwon

71 papers receiving 730 citations

Peers

Hyun Kwon
Comparison fields: 5 of 85
  • Signal Processing 216
  • Artificial Intelligence 469
  • Computer Vision and Pattern Recognition 203
  • Health Informatics 10
  • Computer Networks and Communications 118
Replace Gongshen Liu with:
Gongshen Liu China
Xiaohui Kuang China
Hyunsoo Yoon South Korea
Xuhui Chen China
Joshua Ainslie United States
Ivan Evtimov United States
Aakanksha Chowdhery United States
Tariq Sadad Pakistan
Zuobin Xiong United States
Hyun Kwon relative to Gongshen Liu China Gongshen Liu's profile →
Citations per field
00.5×1.5×2.5×
Gongshen Liu · 1×
Citations per year

Countries citing papers authored by Hyun Kwon

Since Specialization
Citations

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

Fields of papers citing papers by Hyun Kwon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 20 scholars most cited alongside Hyun 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 Hyun Kwon Line = papers co-authored together Hyun Kwon links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 77 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201953
2 202232
3 202032
4 201931
5 201830
6 201927
7 202025
8 202025
9 201821
10 202121
11 202019
12 201819
13 201818
14 202218
15 202117
16 202116
17 201816
18 202115
19 202115
20 202215

About Hyun Kwon

Hyun Kwon is a scholar working on Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Computer Networks and Communications, having authored 77 papers that have together received 744 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (54 papers), Anomaly Detection Techniques and Applications (31 papers), Advanced Malware Detection Techniques (26 papers), Network Security and Intrusion Detection (7 papers), Advanced Neural Network Applications (6 papers), Integrated Circuits and Semiconductor Failure Analysis (6 papers), Digital Media Forensic Detection (6 papers) and Electrostatic Discharge in Electronics (5 papers). The work is most often cited by research in Signal Processing (216 citations), Artificial Intelligence (469 citations), Computer Vision and Pattern Recognition (203 citations), Health Informatics (10 citations) and Computer Networks and Communications (118 citations). Hyun Kwon has collaborated with scholars based in South Korea, Australia and United States. Frequent co-authors include Hyunsoo Yoon, Ki-Woong Park, Daeseon Choi, Jun Lee, Sunghwan Kim, Jang-Woon Baek, Seung‐Ho Lim, Sang‐Hyun Lee, Sang-Hyun Lee and Seung-Hun Nam. Their work appears in journals such as IEEE Access, Multimedia Tools and Applications, Computers & Security, Symmetry and Applied Sciences.

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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