Mu-Chun Su

23 papers receiving 422 citations

Peers

Mu-Chun Su
Comparison fields: 5 of 103
  • Human-Computer Interaction 70
  • Computer Vision and Pattern Recognition 93
  • Neurology 32
  • Artificial Intelligence 126
  • Civil and Structural Engineering 73
Replace Bruno Fernandes with:
Bruno Fernandes Brazil
Afef Abdelkrim Tunisia
Iza Sazanita Isa Malaysia
Sakshi Indolia India
Wen Zhou China
Goran Kvaščev Serbia
Kamal Kumar Ghanshala India
P. Viswanath India
Jeonghong Kim South Korea
Pooja Asopa India
Mu-Chun Su relative to Bruno Fernandes Brazil Bruno Fernandes's profile →
Citations per field
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Bruno Fernandes · 1×
Citations per year

Countries citing papers authored by Mu-Chun Su

Since Specialization
Citations

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

Fields of papers citing papers by Mu-Chun Su

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mu-Chun Su. 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 Mu-Chun Su. The network helps show where Mu-Chun Su may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201669
2 200162
3 201646
4 200935
5 200134
6 200623
7 200521
8 199421
9 201219
10 200115
11 199913
12 201912
13 200311
14 201610
15 20209
16 20108
17 20008
18 20137
19 20146
20 20215

About Mu-Chun Su

Mu-Chun Su is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Human-Computer Interaction, Control and Systems Engineering and Biomedical Engineering, having authored 23 papers that have together received 442 indexed citations. Recurring topics across this work include Face and Expression Recognition (3 papers), Neural Networks and Applications (3 papers), Gaze Tracking and Assistive Technology (3 papers), Hand Gesture Recognition Systems (2 papers), Gait Recognition and Analysis (2 papers), Glaucoma and retinal disorders (2 papers), Flood Risk Assessment and Management (1 paper) and Human Pose and Action Recognition (1 paper). The work is most often cited by research in Human-Computer Interaction (70 citations), Computer Vision and Pattern Recognition (93 citations), Neurology (32 citations), Artificial Intelligence (126 citations) and Civil and Structural Engineering (73 citations). Mu-Chun Su has collaborated with scholars based in Taiwan, Hong Kong and China. Frequent co-authors include Jieh‐Haur Chen, Hsiao-Te Chang, Gwo‐Dong Chen, Shu‐Chien Hsu, Jin‐Chun Lu, Ruijun Cao, Li-Ren Yang, Ching‐Chang Wong, Pa‐Chun Wang and Shih‐Ching Yeh. Their work appears in journals such as Sensors, Automation in Construction, Journal of Housing and the Built Environment, Interactive Learning Environments and Swarm and Evolutionary Computation.

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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