Jun‐Hyeong Do

701 citations
37 papers · 482 · h-index 12

Impact in

Papers in

Jun‐Hyeong Do

35 papers receiving 447 citations

Peers

Jun‐Hyeong Do
Comparison fields: 5 of 89
  • Complementary and alternative medicine 160
  • Human-Computer Interaction 74
  • Computer Vision and Pattern Recognition 142
  • Control and Systems Engineering 64
  • Occupational Therapy 10
Replace Hari Singh with:
Hari Singh India
S. Poonguzhali India
ChangHwan Kim South Korea
Huihui Li China
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Ajat Shatru Arora India
Jianliang Min China
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Allam Jaya Prakash India
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Jun‐Hyeong Do relative to Hari Singh India Hari Singh's profile →
Citations per field
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Citations per year

Countries citing papers authored by Jun‐Hyeong Do

Since Specialization
Citations

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

Fields of papers citing papers by Jun‐Hyeong Do

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jun‐Hyeong Do. 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 Jun‐Hyeong Do. The network helps show where Jun‐Hyeong Do may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201274
2 200666
3 201143
4 201843
5 200526
6 200524
7 200822
8 200522
9 201218
10 200815
11 201314
12 201214
13 201311
14 201210
15 201610
16 20089
17
Soft Remote Control System using Hand Pointing Gestures
20027
18 20076
19 20175
20
User-Friendly Interaction/Interface Control of Intelligent Home for Movement-Disabled People
20035

About Jun‐Hyeong Do

Jun‐Hyeong Do is a scholar working on Complementary and alternative medicine, Human-Computer Interaction, Control and Systems Engineering, Computer Vision and Pattern Recognition and Molecular Biology, having authored 37 papers that have together received 482 indexed citations. Recurring topics across this work include Traditional Chinese Medicine Studies (14 papers), Robotics and Automated Systems (9 papers), Hand Gesture Recognition Systems (8 papers), Gaze Tracking and Assistive Technology (6 papers), Context-Aware Activity Recognition Systems (5 papers), Ginseng Biological Effects and Applications (4 papers), Stroke Rehabilitation and Recovery (4 papers) and Social Robot Interaction and HRI (4 papers). The work is most often cited by research in Complementary and alternative medicine (160 citations), Human-Computer Interaction (74 citations), Computer Vision and Pattern Recognition (142 citations), Control and Systems Engineering (64 citations) and Occupational Therapy (10 citations). Jun‐Hyeong Do has collaborated with scholars based in South Korea, United States and Bulgaria. Frequent co-authors include Jong Yeol Kim, Zeungnam Bien, Boncho Ku, Jun-Su Jang, Eun-Su Jang, Jin-Woo Jung, Kwang‐Hyun Park, Hyong-Euk Lee, Duong Duc Pham and Ki‐Hong Park. Their work appears in journals such as Evidence-based Complementary and Alternative Medicine, International Journal of Computational Intelligence Systems, Sensors, Autonomous Robots and IEEE Transactions on Industrial Electronics.

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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