Yu‐Lin Wei

43 papers receiving 682 citations

Peers

Yu‐Lin Wei
Comparison fields: 5 of 83
  • Signal Processing 102
  • Human-Computer Interaction 42
  • Instrumentation 22
  • Electrical and Electronic Engineering 340
  • Computer Vision and Pattern Recognition 95
Replace Pengcheng Wang with:
Pengcheng Wang China
Yue Chen China
Xuansong Xie China
Shan An China
Yunxin Li China
Wei H. Yang China
Bilal Hassan China
Yoshito Mekada Japan
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Yu‐Lin Wei relative to Pengcheng Wang China Pengcheng Wang's profile →
Citations per field
00.5×5×10×12.8×
Pengcheng Wang · 1×
Citations per year

Countries citing papers authored by Yu‐Lin Wei

Since Specialization
Citations

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

Fields of papers citing papers by Yu‐Lin Wei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015123
2 202161
3 202056
4 202050
5 201547
6 201739
7 202034
8 201633
9 201933
10 201926
11 201822
12 202220
13 201617
14 202114
15 202110
16 201410
17 20219
18 20219
19 20178
20 20237

About Yu‐Lin Wei

Yu‐Lin Wei is a scholar working on Signal Processing, Cardiology and Cardiovascular Medicine, Electrical and Electronic Engineering, Ceramics and Composites and Computer Vision and Pattern Recognition, having authored 47 papers that have together received 690 indexed citations. Recurring topics across this work include Indoor and Outdoor Localization Technologies (12 papers), Optical Wireless Communication Technologies (7 papers), Speech and Audio Processing (6 papers), Nuclear Materials and Properties (4 papers), Advanced ceramic materials synthesis (3 papers), Advanced materials and composites (3 papers), Tactile and Sensory Interactions (3 papers) and Fusion materials and technologies (3 papers). The work is most often cited by research in Signal Processing (102 citations), Human-Computer Interaction (42 citations), Instrumentation (22 citations), Electrical and Electronic Engineering (340 citations) and Computer Vision and Pattern Recognition (95 citations). Yu‐Lin Wei has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Hsin‐Mu Tsai, Romit Roy Choudhury, Kate Ching‐Ju Lin, Zhijian Yang, Hsin‐I Wu, Jay Prakash, Ailing Chen, Sheng Shen, Haitham Hassanieh and Sheng Shen. Their work appears in journals such as Journal of Nuclear Materials, International journal of cardiac imaging, Annals of Translational Medicine, Ceramics International and Journal of Alloys and Compounds.

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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