TaeChoong Chung

1.2k citations
61 papers · 727 · h-index 14

Impact in

Papers in

TaeChoong Chung

59 papers receiving 683 citations

Peers

TaeChoong Chung
Comparison fields: 5 of 92
  • Computer Vision and Pattern Recognition 234
  • Computer Networks and Communications 177
  • Artificial Intelligence 216
  • Civil and Structural Engineering 103
  • Control and Systems Engineering 105
Replace Chenglie Du with:
Chenglie Du China
Antonio Berlanga Spain
Jingling Yuan China
Zeinab Montazeri Iran
Martin Fleury United Kingdom
Yuchen Li China
Albert Esterline United States
Xian-Bing Meng China
Liguo Yao China
TaeChoong Chung relative to Chenglie Du China Chenglie Du's profile →
Citations per field
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Citations per year

Countries citing papers authored by TaeChoong Chung

Since Specialization
Citations

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

Fields of papers citing papers by TaeChoong Chung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 61 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201287
2 202085
3 200468
4 201449
5 201842
6 201728
7 201922
8 201122
9 201720
10 201718
11 201716
12 200815
13 201315
14 202015
15 202012
16 201912
17
An online complete coverage algorithm for cleaning robots based on boustrophedon motions and A* search
201211
18 201911
19 200610
20 202110

About TaeChoong Chung

TaeChoong Chung is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications, Control and Systems Engineering and Computational Theory and Mathematics, having authored 61 papers that have together received 727 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (15 papers), Robotic Path Planning Algorithms (8 papers), Robotics and Sensor-Based Localization (6 papers), Game Theory and Voting Systems (5 papers), Complexity and Algorithms in Graphs (5 papers), Metaheuristic Optimization Algorithms Research (4 papers), Robot Manipulation and Learning (4 papers) and Auction Theory and Applications (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (234 citations), Computer Networks and Communications (177 citations), Artificial Intelligence (216 citations), Civil and Structural Engineering (103 citations) and Control and Systems Engineering (105 citations). TaeChoong Chung has collaborated with scholars based in South Korea, Vietnam and United Kingdom. Frequent co-authors include Ngo Anh Vien, Viet-Hung Dang, Sanghak Lee, SeungGwan Lee, Quang Dang Nguyen, Sungyoung Lee, S. K. Choi, Kiet Tran, Bryan Magee and Khoa Tan Nguyen. Their work appears in journals such as Applied Intelligence, IEEE Access, Applied Sciences, Symmetry and Information 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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