Bing Wei

839 citations
47 papers · 540 · h-index 13

Impact in

Papers in

Bing Wei

43 papers receiving 528 citations

Peers

Bing Wei
Comparison fields: 5 of 85
  • Industrial and Manufacturing Engineering 207
  • Media Technology 75
  • Computer Vision and Pattern Recognition 157
  • Artificial Intelligence 114
  • Computational Mathematics 2
Replace Matthias Rätsch with:
Matthias Rätsch Germany
Xinyi Gong China
Erhu Zhang China
Guifang Duan China
Qingsheng Xie China
Bailin Li China
Kazım Hanbay Türkiye
Cien Fan China
Bing Wei relative to Matthias Rätsch Germany Matthias Rätsch's profile →
Citations per field
00.5×1.5×1.8×
Matthias Rätsch · 1×
Citations per year

Countries citing papers authored by Bing Wei

Since Specialization
Citations

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

Fields of papers citing papers by Bing Wei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Bing 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 Bing Wei Line = papers co-authored together Bing 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 201974
2 201865
3 201739
4 202135
5 202033
6 202028
7 202228
8 202026
9 202121
10 202120
11 202215
12 202212
13 202012
14 202212
15 202211
16 202410
17 20229
18 20238
19 20237
20 20236

About Bing Wei

Bing Wei is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Industrial and Manufacturing Engineering, Media Technology and Biomedical Engineering, having authored 47 papers that have together received 540 indexed citations. Recurring topics across this work include Industrial Vision Systems and Defect Detection (15 papers), Image Processing Techniques and Applications (9 papers), Advanced Neural Network Applications (6 papers), Domain Adaptation and Few-Shot Learning (5 papers), Anomaly Detection Techniques and Applications (5 papers), Fault Detection and Control Systems (4 papers), Non-Invasive Vital Sign Monitoring (4 papers) and Visual Attention and Saliency Detection (4 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (207 citations), Media Technology (75 citations), Computer Vision and Pattern Recognition (157 citations), Artificial Intelligence (114 citations) and Computational Mathematics (2 citations). Bing Wei has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Kuangrong Hao, Xue‐song Tang, Lei Gao, Yudi Zhao, Haibo He, Xiaopei Wu, Yongsheng Ding, Biao Huang, Fan Guo and Chao Zhang. Their work appears in journals such as Neural Networks, Neurocomputing, Textile Research Journal, Information Sciences and IEEE Transactions on Cognitive and Developmental 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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