Xiaoming Wei

2.2k citations
14 papers · 232 · 1 hit paper · h-index 8

Impact in

Papers in

Xiaoming Wei

13 papers receiving 230 citations

Xiaoming Wei's Hit Papers

Large Scale Visual Food Recognition 2023 · 138 citations
1380+1+2Years since publication4080120

Peers

Xiaoming Wei
Comparison fields: 5 of 65
  • Computer Graphics and Computer-Aided Design 13
  • Computer Vision and Pattern Recognition 64
  • Public Health, Environmental and Occupational Health 56
  • Analytical Chemistry 18
  • Biomedical Engineering 71
Replace Takumi Ege with:
Takumi Ege Japan
Dario Allegra Italy
Arjun Karpur United States
Fangting Xia United States
Zeman Shao United States
R. Parameswari India
Wenxuan Li China
Boyang Deng United States
Nishant Shukla India
Marika Valentino Italy
Xiaoming Wei relative to Takumi Ege Japan Takumi Ege's profile →
Citations per field
00.5×4.1×
Takumi Ege · 1×
Citations per year

Countries citing papers authored by Xiaoming Wei

Since Specialization
Citations

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

Fields of papers citing papers by Xiaoming Wei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

14 of 14 papers shown
#Work
1
Large Scale Visual Food Recognition
Hit paper breakdown →
2023138
2 202022
3 200312
4 202111
5 202311
6 20238
7 20227
8 20227
9 20126
10 20253
11 20253
12 20053
13 20251
14 20240

About Xiaoming Wei

Xiaoming Wei is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Graphics and Computer-Aided Design, Astronomy and Astrophysics and Oceanography, having authored 14 papers that have together received 232 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (4 papers), Advanced Image and Video Retrieval Techniques (4 papers), Advanced Image Processing Techniques (2 papers), Computer Graphics and Visualization Techniques (2 papers), Optical measurement and interference techniques (1 paper), Image Enhancement Techniques (1 paper), Advanced Photocatalysis Techniques (1 paper) and Data Visualization and Analytics (1 paper). The work is most often cited by research in Computer Graphics and Computer-Aided Design (13 citations), Computer Vision and Pattern Recognition (64 citations), Public Health, Environmental and Occupational Health (56 citations), Analytical Chemistry (18 citations) and Biomedical Engineering (71 citations). Xiaoming Wei has collaborated with scholars based in China, United States and Netherlands. Frequent co-authors include Xiaolin Wei, Liping Kang, Shuqiang Jiang, Weiqing Min, Yuxin Liu, Zhiling Wang, Menghan Sun, Na Lu, Peng Zhang and Zhenyi Zhang. Their work appears in journals such as Agricultural Water Management, Remote Sensing, Polymers, Optik and IEEE Transactions on Pattern Analysis and Machine Intelligence.

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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