Mingxing Wen

535 citations
39 papers · 363 indexed · h-index 12
Topics
Robotics and Sensor-Based Localization (27 papers)Robotic Path Planning Algorithms (16 papers)Indoor and Outdoor Localization Technologies (8 papers)
Partner nations
SingaporeChinaJapan

In The Last Decade

Mingxing Wen

33 papers receiving 357 citations

Peers

Mingxing Wen
Comparison fields: 5 of 44
  • Aerospace Engineering 281
  • Computer Vision and Pattern Recognition 208
  • Electrical and Electronic Engineering 82
  • Ocean Engineering 42
  • Control and Systems Engineering 39
Replace Josip Ćesić with:
Josip Ćesić Croatia
Chule Yang Singapore
Fanfei Chen United States
David J. Yoon Canada
Janusz Będkowski Poland
Ian Baldwin United Kingdom
Yingying Ran China
René Wagner Germany
Julien Moras France
Mingxing Wen relative to Josip Ćesić Croatia Josip Ćesić's profile →
Citations per field
00.5×6.4×
Josip Ćesić · 1×
Citations per year

Countries citing papers authored by Mingxing Wen

Since Specialization
Citations

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

Fields of papers citing papers by Mingxing Wen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mingxing Wen

This figure shows the co-authorship network connecting the top 25 collaborators of Mingxing Wen. A scholar is included among the top collaborators of Mingxing Wen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mingxing Wen. Mingxing Wen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 0
3 0
4 2
5 2
6 0
7 1
8 2
9 1
10 52
11 6
12 11
13 24
14 15
15 4
16 11
17 32
18 3
19 2
20 1

About Mingxing Wen

Mingxing Wen is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Ocean Engineering, having authored 39 papers that have together received 363 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (27 papers), Robotic Path Planning Algorithms (16 papers) and Indoor and Outdoor Localization Technologies (8 papers). The work is most often cited by research in Aerospace Engineering (281 citations), Computer Vision and Pattern Recognition (208 citations) and Geology (35 citations). Mingxing Wen has collaborated with scholars based in Singapore, China and Japan. Frequent co-authors include Danwei Wang, Yufeng Yue, Chule Yang, Zhenyu Wu, Jun Zhang, Guohao Peng, Chunyang Zhao, Yuanzhe Wang, Yiyao Liu and Danwei Wang. Their work appears in journals such as IEEE Transactions on Industrial Electronics, Frontiers in Microbiology and IEEE Transactions on Intelligent Transportation 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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