Kwee-Bo Sim

2.1k citations
198 papers · 1.6k · h-index 17

Impact in

Papers in

Kwee-Bo Sim

161 papers receiving 1.4k citations

Peers

Kwee-Bo Sim
Comparison fields: 5 of 124
  • Cognitive Neuroscience 396
  • Computer Vision and Pattern Recognition 426
  • Human-Computer Interaction 115
  • Signal Processing 185
  • Artificial Intelligence 469
Replace Shyamanta M. Hazarika with:
Shyamanta M. Hazarika India
Jingwei Too Malaysia
Reza Ebrahimpour Iran
Rui Yan China
Anikó Ekárt United Kingdom
Jyh‐Yeong Chang Taiwan
Zhongmin Wang China
M. A. H. Akhand Bangladesh
Osama Ahmad Alomari Jordan
Khaled Elleithy United States
Kwee-Bo Sim relative to Shyamanta M. Hazarika India Shyamanta M. Hazarika's profile →
Citations per field
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Shyamanta M. Hazarika · 1×
Citations per year

Countries citing papers authored by Kwee-Bo Sim

Since Specialization
Citations

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

Fields of papers citing papers by Kwee-Bo Sim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kwee-Bo Sim. 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 Kwee-Bo Sim. The network helps show where Kwee-Bo Sim may publish in the future.

Co-authors

The 25 scholars most cited alongside Kwee-Bo Sim, 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 Kwee-Bo Sim Line = papers co-authored together Kwee-Bo Sim links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 198 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010183
2 2017112
3 2013109
4 2009106
5 201895
6 200659
7 201039
8 200633
9 200830
10 200226
11 200323
12 201022
13 201321
14 200721
15 200819
16
Game Theory Based Coevolutionary Algorithm: A New Computational Coevolutionary Approach
200416
17 202116
18 200416
19 200216
20 200914

About Kwee-Bo Sim

Kwee-Bo Sim is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Cognitive Neuroscience, Signal Processing and Control and Systems Engineering, having authored 198 papers that have together received 1.6k indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (53 papers), Blind Source Separation Techniques (28 papers), Gaze Tracking and Assistive Technology (24 papers), Evolutionary Algorithms and Applications (21 papers), Face and Expression Recognition (19 papers), Neural Networks and Applications (19 papers), Metaheuristic Optimization Algorithms Research (18 papers) and Neuroscience and Neural Engineering (14 papers). The work is most often cited by research in Cognitive Neuroscience (396 citations), Computer Vision and Pattern Recognition (426 citations), Human-Computer Interaction (115 citations), Signal Processing (185 citations) and Artificial Intelligence (469 citations). Kwee-Bo Sim has collaborated with scholars based in South Korea, United States and Japan. Frequent co-authors include Kwang-Eun Ko, Zong Woo Geem, Xinyang Yu, Seung Min Park, Fumio Harashima, Chang-Hyun Park, Dong-Wook Lee, Dong-Wook Lee, Dong-Wook Lee and Ji‐Yoon Kim. Their work appears in journals such as Optik, Electronics Letters, Electronics, International Journal of Fuzzy Logic and Intelligent Systems and Lecture notes in computer science.

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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