Xiaowei Yang

2.2k citations
92 papers · 1.7k · h-index 23

Impact in

Papers in

Xiaowei Yang

90 papers receiving 1.6k citations

Peers

Xiaowei Yang
Comparison fields: 5 of 138
  • Computational Mathematics 53
  • Computer Vision and Pattern Recognition 558
  • Artificial Intelligence 795
  • Media Technology 107
  • Computational Theory and Mathematics 185
Replace Nan Zhang with:
Nan Zhang China
Si Wu China
Yitian Xu China
Mineichi Kudo Japan
Suresh Chandra India
Qingyao Wu China
Chong‐Ho Choi South Korea
宏治 津田 Japan
Fanzhang Li China
Yong Luo China
Xiaowei Yang relative to Nan Zhang China Nan Zhang's profile →
Citations per field
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Nan Zhang · 1×
Citations per year

Countries citing papers authored by Xiaowei Yang

Since Specialization
Citations

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

Fields of papers citing papers by Xiaowei Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 92 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010227
2 2014117
3 2013101
4 200879
5 201978
6 202152
7 202046
8 202043
9 200843
10 201936
11 201935
12 200934
13 200932
14 201832
15 200931
16 200329
17 201529
18 201428
19 201628
20 202328

About Xiaowei Yang

Xiaowei Yang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Control and Systems Engineering, Molecular Biology and Information Systems, having authored 92 papers that have together received 1.7k indexed citations. Recurring topics across this work include Face and Expression Recognition (28 papers), Advanced Algorithms and Applications (19 papers), Machine Learning and ELM (11 papers), Image and Signal Denoising Methods (9 papers), Text and Document Classification Technologies (9 papers), Domain Adaptation and Few-Shot Learning (7 papers), Metaheuristic Optimization Algorithms Research (7 papers) and Spectroscopy and Chemometric Analyses (6 papers). The work is most often cited by research in Computational Mathematics (53 citations), Computer Vision and Pattern Recognition (558 citations), Artificial Intelligence (795 citations), Media Technology (107 citations) and Computational Theory and Mathematics (185 citations). Xiaowei Yang has collaborated with scholars based in China, Australia and United Kingdom. Frequent co-authors include Lifang He, Zhifeng Hao, Jie Lü, Guangquan Zhang, Han Huang, Jun Ma, Yi Xiang, Sentao Chen, Le Han and Xiaolan Liu. Their work appears in journals such as Neurocomputing, IEEE Transactions on Image Processing, IEEE Transactions on Neural Networks and Learning Systems, Soft Computing and Pattern Recognition.

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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