Sungho Suh

67 papers receiving 1.0k citations

Sungho Suh's Hit Papers

Human-centric artificial intelligence architecture for industry 5.0 applications 2022 · 159 citations
1590+1+2Years since publication50100150

Peers

Sungho Suh
Comparison fields: 5 of 123
  • Industrial and Manufacturing Engineering 123
  • Media Technology 88
  • Human-Computer Interaction 51
  • Computer Vision and Pattern Recognition 188
  • Instrumentation 29
Replace Mohammad Farukh Hashmi with:
Mohammad Farukh Hashmi India
João Monteiro Portugal
Delong Zhu Hong Kong
Hamid Tairi Morocco
Kyeong-Beom Park South Korea
Yang Wen China
Omar Elharrouss Qatar
Rahee Walambe India
Byung Cheol Song South Korea
Sungho Suh relative to Mohammad Farukh Hashmi India Mohammad Farukh Hashmi's profile →
Citations per field
00.5×7.3×
Mohammad Farukh Hashmi · 1×
Citations per year

Countries citing papers authored by Sungho Suh

Since Specialization
Citations

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

Fields of papers citing papers by Sungho Suh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 79 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Human-centric artificial intelligence architecture for industry 5.0 applications
Hit paper breakdown →
2022159
2 1998103
3 201192
4 202187
5 202068
6 202256
7 199653
8 201052
9 201950
10 202229
11 202125
12 202023
13 202121
14 201917
15 202216
16 201116
17 202315
18 202313
19 202413
20 200512

About Sungho Suh

Sungho Suh is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Artificial Intelligence, Biomedical Engineering and Cellular and Molecular Neuroscience, having authored 79 papers that have together received 1.0k indexed citations. Recurring topics across this work include Context-Aware Activity Recognition Systems (18 papers), Human Pose and Action Recognition (12 papers), CCD and CMOS Imaging Sensors (12 papers), Anomaly Detection Techniques and Applications (9 papers), Neuroscience and Neural Engineering (8 papers), Non-Invasive Vital Sign Monitoring (7 papers), Industrial Vision Systems and Defect Detection (7 papers) and Hand Gesture Recognition Systems (6 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (123 citations), Media Technology (88 citations), Human-Computer Interaction (51 citations), Computer Vision and Pattern Recognition (188 citations) and Instrumentation (29 citations). Sungho Suh has collaborated with scholars based in Germany, South Korea and United States. Frequent co-authors include Paul Lukowicz, Yong Oh Lee, Vítor Fortes Rey, Shinya Itoh, Shoji Kawahito, Bo Zhou, Satoshi Aoyama, Seul Kee Kim, I W Choo and Keigo Isobe. Their work appears in journals such as Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies, Knowledge-Based Systems, Expert Systems with Applications, Neural Networks and Radiology.

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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