Nak Young Chong

173 papers receiving 1.7k citations

Peers

Nak Young Chong
Comparison fields: 5 of 121
  • Control and Systems Engineering 544
  • Computer Vision and Pattern Recognition 521
  • Mechanical Engineering 404
  • Biomedical Engineering 387
  • Computer Networks and Communications 364
Replace Takehiro Sato with:
Takehiro Sato Japan
Taşkın Padır United States
Kai‐Tai Song Taiwan
Odest Chadwicke Jenkins United States
Karsten Berns Germany
Kosuke Sekiyama Japan
Renato Zaccaria Italy
Fumio Harashima Japan
Nicola Bellotto United Kingdom
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Nak Young Chong relative to Takehiro Sato Japan Takehiro Sato's profile →
Citations per field
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Citations per year

Countries citing papers authored by Nak Young Chong

Since Specialization
Citations

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

Fields of papers citing papers by Nak Young Chong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nak Young Chong. 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 Nak Young Chong. The network helps show where Nak Young Chong may publish in the future.

Co-authorship network of co-authors of Nak Young Chong

This figure shows the co-authorship network connecting the top 25 collaborators of Nak Young Chong. A scholar is included among the top collaborators of Nak Young Chong based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Nak Young Chong. Nak Young Chong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
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A distributed algorithm for the coordination of dynamic barricades composed of autonomous mobile robots
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13
RF Power Detector for Location Sensing
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14 1
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Object Directive Manipulation Through RFID
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Knowledge Distributed Robot Control Framework
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Multi-Camera Vision System for Tele-Robotics
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COLLISION-FREE TRAJECTORY PLANNING FOR DUAL ROBOT ARMS
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About Nak Young Chong

Nak Young Chong is a scholar working on Computer Vision and Pattern Recognition, Control and Systems Engineering and Computer Networks and Communications, having authored 184 papers that have together received 1.8k indexed citations. Recurring topics across this work include Robot Manipulation and Learning (45 papers), Robotic Path Planning Algorithms (35 papers) and Modular Robots and Swarm Intelligence (31 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (521 citations), Control and Systems Engineering (544 citations) and Human-Computer Interaction (107 citations). Nak Young Chong has collaborated with scholars based in Japan, South Korea and United States. Frequent co-authors include Myung-Sik Kim, Geun-Ho Lee, Geun-Ho Lee, Sungmoon Jeong, Armağan Elibol, K. Tanie, Kohtaro Ohba, Woosung Yang, Tetsuo Kotoku and K. Komoriya. Their work appears in journals such as IEEE Transactions on Industrial Informatics, IEEE Transactions on Robotics and IEEE/ASME Transactions on Mechatronics.

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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