Wei‐Chung Lin

620 citations
42 papers · 396 · h-index 11

Impact in

Papers in

Wei‐Chung Lin

35 papers receiving 374 citations

Peers

Wei‐Chung Lin
Comparison fields: 5 of 79
  • Computer Vision and Pattern Recognition 244
  • Computer Graphics and Computer-Aided Design 39
  • Media Technology 59
  • Industrial and Manufacturing Engineering 39
  • Computational Mechanics 54
Replace Oana G. Cula with:
Oana G. Cula United States
Jitesh Jain India
Stephan J. Garbin United Kingdom
Pengfei Fan China
Jack Perkins Australia
Raghava Kondepudy United States
Xiaoyu Xiang United States
H.-S. Don United States
Erum Arif Khan United States
Hyunwoo Kim South Korea
Wei‐Chung Lin relative to Oana G. Cula United States Oana G. Cula's profile →
Citations per field
00.5×2.8×
Oana G. Cula · 1×
Citations per year

Countries citing papers authored by Wei‐Chung Lin

Since Specialization
Citations

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

Fields of papers citing papers by Wei‐Chung Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wei‐Chung Lin. 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 Wei‐Chung Lin. The network helps show where Wei‐Chung Lin may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199171
2 198955
3 198438
4 199235
5 199428
6 199217
7 200316
8 200313
9 199113
10 200311
11 199311
12 20039
13 19958
14 19867
15 19976
16 19955
17 19965
18 19975
19 19915
20 20025

About Wei‐Chung Lin

Wei‐Chung Lin is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computational Mechanics, Aerospace Engineering and Biomedical Engineering, having authored 42 papers that have together received 396 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (13 papers), Image Retrieval and Classification Techniques (8 papers), Neural Networks and Applications (6 papers), Optical measurement and interference techniques (6 papers), Robotics and Sensor-Based Localization (6 papers), Image and Object Detection Techniques (5 papers), 3D Shape Modeling and Analysis (5 papers) and Advanced Vision and Imaging (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (244 citations), Computer Graphics and Computer-Aided Design (39 citations), Media Technology (59 citations), Industrial and Manufacturing Engineering (39 citations) and Computational Mechanics (54 citations). Wei‐Chung Lin has collaborated with scholars based in United States, Taiwan and South Korea. Frequent co-authors include Chin-Tu Chen, King‐Sun Fu, Eric Chen-Kuo Tsao, C. R. Liu, Hsiu‐Fu Hsu, Chin‐Tu Chen, Liang-Hua Chen, Charles A. Pelizzari, Bharat B. Mittal and M. Piket-May. Their work appears in journals such as Liquid Crystals, International Journal of Imaging Systems and Technology, Chemistry of Materials, Applied Sciences and IEEE Transactions on Biomedical Engineering.

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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