Shih‐Hsiung Lee

578 citations
51 papers · 352 indexed · h-index 12

Shih‐Hsiung Lee

40 papers receiving 333 citations

Peers

Shih‐Hsiung Lee
Comparison fields: 5 of 91
  • Transportation 25
  • Computer Vision and Pattern Recognition 68
  • Industrial and Manufacturing Engineering 31
  • Computer Networks and Communications 60
  • Information Systems 57
Replace Qingjun Wang with:
Qingjun Wang China
Wattanapong Kurdthongmee Thailand
Fotios Zantalis Greece
Hasan U. Zaman Bangladesh
Sotiris Karabetsos Greece
Carlos Ruiz United States
Medhat Awadalla Egypt
Yanli Shao China
Paulo Sérgio Cugnasca Brazil
Guohui Zhou China
Shih‐Hsiung Lee relative to Qingjun Wang China Qingjun Wang's profile →
Citations per field
00.5×2.6×
Qingjun Wang · 1×
Citations per year

Countries citing papers authored by Shih‐Hsiung Lee

Since Specialization
Citations

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

Fields of papers citing papers by Shih‐Hsiung Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shih‐Hsiung Lee. 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 Shih‐Hsiung Lee. The network helps show where Shih‐Hsiung Lee may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20251
3 20240
4 202312
5 202311
6 20235
7 202323
8 202317
9 20232
10 20230
11 202214
12 202219
13 20226
14 20213
15 20217
16 20219
17 202036
18 20203
19 201836
20 201726

About Shih‐Hsiung Lee

Shih‐Hsiung Lee is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition and Signal Processing, having authored 51 papers that have together received 352 indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (4 papers), Advanced Neural Network Applications (4 papers), Anomaly Detection Techniques and Applications (3 papers), Smart Grid Security and Resilience (3 papers), Biometric Identification and Security (3 papers), IoT-based Smart Home Systems (3 papers), Handwritten Text Recognition Techniques (3 papers) and Industrial Vision Systems and Defect Detection (3 papers). The work is most often cited by research in Transportation (25 citations), Computer Vision and Pattern Recognition (68 citations) and Industrial and Manufacturing Engineering (31 citations). Shih‐Hsiung Lee has collaborated with scholars based in Taiwan and Yemen. Frequent co-authors include Chu‐Sing Yang, Ting‐Wei Hou, Yusheng Yang, Yueh‐Min Huang, Tien‐Hsiang Chang, Tsung-Yin Ou, Chiu‐Chu Hwang, Yung‐Hsiang Tsai, Ko-Wei Huang and Yi‐Chen Lee. Their work appears in journals such as Applied Sciences, Sensors, Energies, IEEE Transactions on Intelligent Transportation Systems and International Journal of Computational Intelligence Systems.

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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