Seok-Jun Bu

927 citations
39 papers · 718 · h-index 12

Impact in

Papers in

Seok-Jun Bu

35 papers receiving 689 citations

Peers

Seok-Jun Bu
Comparison fields: 5 of 71
  • Signal Processing 360
  • Computer Networks and Communications 340
  • Artificial Intelligence 402
  • Information Systems 191
  • Computer Vision and Pattern Recognition 92
Replace Zahoor Ur Rehman with:
Zahoor Ur Rehman Pakistan
Amit Kumar Sikder United States
Shang Gao Hong Kong
Kyounggon Kim Saudi Arabia
Soltan Abed Alharbi Saudi Arabia
Zuobin Xiong United States
Ranbir Singh Batth India
Meng-Yen Hsieh Taiwan
Pei Ke China
Seok-Jun Bu relative to Zahoor Ur Rehman Pakistan Zahoor Ur Rehman's profile →
Citations per field
00.5×2×3×3.5×
Zahoor Ur Rehman · 1×
Citations per year

Countries citing papers authored by Seok-Jun Bu

Since Specialization
Citations

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

Fields of papers citing papers by Seok-Jun Bu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Seok-Jun Bu. 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 Seok-Jun Bu. The network helps show where Seok-Jun Bu may publish in the future.

Co-authors

The 5 scholars most cited alongside Seok-Jun Bu, 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 Seok-Jun Bu Line = papers co-authored together Seok-Jun Bu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018209
2 202074
3 201773
4 201963
5 202141
6 202039
7 201827
8 202226
9 201716
10 202115
11 202213
12 201813
13 202011
14 202311
15 202010
16 201810
17 20218
18 20238
19 20196
20 20185

About Seok-Jun Bu

Seok-Jun Bu is a scholar working on Signal Processing, Computer Networks and Communications, Artificial Intelligence, Information Systems and Automotive Engineering, having authored 39 papers that have together received 718 indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (15 papers), Advanced Malware Detection Techniques (10 papers), Spam and Phishing Detection (9 papers), Anomaly Detection Techniques and Applications (5 papers), Misinformation and Its Impacts (5 papers), Vehicle Noise and Vibration Control (5 papers), Speech and Audio Processing (5 papers) and Text and Document Classification Technologies (4 papers). The work is most often cited by research in Signal Processing (360 citations), Computer Networks and Communications (340 citations), Artificial Intelligence (402 citations), Information Systems (191 citations) and Computer Vision and Pattern Recognition (92 citations). Seok-Jun Bu has collaborated with scholars based in South Korea. Frequent co-authors include Sung‐Bae Cho, Sung-Bae Cho, Jin Young Kim, Won Tae Jeong and Jaeil Park. Their work appears in journals such as Electronics, Information Sciences, Neurocomputing, Lecture notes in computer science and Logic Journal of IGPL.

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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