Seok‐Bum Ko

3.6k citations
192 papers · 2.4k · h-index 23

Impact in

Papers in

Seok‐Bum Ko

177 papers receiving 2.3k citations

Peers

Seok‐Bum Ko
Comparison fields: 5 of 129
  • Hardware and Architecture 338
  • Computational Theory and Mathematics 527
  • Signal Processing 290
  • Computer Vision and Pattern Recognition 511
  • Health Informatics 30
Replace Tughrul Arslan with:
Tughrul Arslan United Kingdom
Abdellatif Mtibaa Tunisia
Xuan Zeng China
Khan A. Wahid Canada
Miriam Leeser United States
Domenico Grimaldi Italy
Gerd Ascheid Germany
Jayaraman J. Thiagarajan United States
Yik‐Chung Wu Hong Kong
Hassan Qjidaa Morocco
Seok‐Bum Ko relative to Tughrul Arslan United Kingdom Tughrul Arslan's profile →
Citations per field
00.5×4.3×
Tughrul Arslan · 1×
Citations per year

Countries citing papers authored by Seok‐Bum Ko

Since Specialization
Citations

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

Fields of papers citing papers by Seok‐Bum Ko

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Seok‐Bum Ko. 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‐Bum Ko. The network helps show where Seok‐Bum Ko may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 192 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017266
2 2020131
3 202294
4 201294
5 201984
6 201765
7 200858
8 201950
9 202047
10 202044
11 202042
12 201938
13 202036
14 201135
15 202032
16 201231
17 202030
18 202127
19 202126
20 200925

About Seok‐Bum Ko

Seok‐Bum Ko is a scholar working on Electrical and Electronic Engineering, Computational Theory and Mathematics, Computer Vision and Pattern Recognition, Signal Processing and Hardware and Architecture, having authored 192 papers that have together received 2.4k indexed citations. Recurring topics across this work include Low-power high-performance VLSI design (50 papers), Numerical Methods and Algorithms (45 papers), Digital Filter Design and Implementation (32 papers), Parallel Computing and Optimization Techniques (21 papers), Advanced Memory and Neural Computing (21 papers), Analog and Mixed-Signal Circuit Design (15 papers), Interconnection Networks and Systems (14 papers) and Advanced Image Processing Techniques (10 papers). The work is most often cited by research in Hardware and Architecture (338 citations), Computational Theory and Mathematics (527 citations), Signal Processing (290 citations), Computer Vision and Pattern Recognition (511 citations) and Health Informatics (30 citations). Seok‐Bum Ko has collaborated with scholars based in Canada, India and South Korea. Frequent co-authors include S. Venkatachalam, Younhee Choi, Hao Zhang, S. Deivalakshmi, Khan A. Wahid, Gong Yong Jin, Hyuk-Jae Lee, Qiao Zhang, Han Liu and Dongdong Chen. Their work appears in journals such as Multimedia Tools and Applications, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, IEEE Transactions on Circuits & Systems II Express Briefs, IEEE Transactions on Computers and IET Intelligent Transport Systems.

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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