Xiaonian Wang

624 citations
37 papers · 446 · h-index 10

Impact in

Papers in

Xiaonian Wang

36 papers receiving 425 citations

Peers

Xiaonian Wang
Comparison fields: 5 of 82
  • Automotive Engineering 121
  • Environmental Engineering 132
  • Computer Vision and Pattern Recognition 147
  • Geology 36
  • Instrumentation 17
Replace Feilong Yan with:
Feilong Yan China
Stefan Hrabar Australia
Fernando Vanegas Australia
Vincent Frémont France
Duong-Van Nguyen Germany
Brandon Stark United States
Hoam Chung Australia
Torsten Merz Australia
Xiaonian Wang relative to Feilong Yan China Feilong Yan's profile →
Citations per field
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Feilong Yan · 1×
Citations per year

Countries citing papers authored by Xiaonian Wang

Since Specialization
Citations

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

Fields of papers citing papers by Xiaonian Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018124
2 202174
3 200538
4 201531
5 201530
6 201517
7 201415
8 202314
9 200513
10 200313
11 20177
12 20187
13 20177
14 20166
15 20116
16 20245
17 20204
18 20084
19 20104
20 20223

About Xiaonian Wang

Xiaonian Wang is a scholar working on Computer Vision and Pattern Recognition, Automotive Engineering, Aerospace Engineering, Electrical and Electronic Engineering and Control and Systems Engineering, having authored 37 papers that have together received 446 indexed citations. Recurring topics across this work include Autonomous Vehicle Technology and Safety (8 papers), Remote Sensing and LiDAR Applications (6 papers), Robotics and Sensor-Based Localization (6 papers), Video Surveillance and Tracking Methods (5 papers), Robotic Path Planning Algorithms (3 papers), Advanced Neural Network Applications (3 papers), Advanced Vision and Imaging (3 papers) and Phase Equilibria and Thermodynamics (3 papers). The work is most often cited by research in Automotive Engineering (121 citations), Environmental Engineering (132 citations), Computer Vision and Pattern Recognition (147 citations), Geology (36 citations) and Instrumentation (17 citations). Xiaonian Wang has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Jun Wang, Yihuan Zhang, John M. Dolan, Zuren Feng, Yuanjing Feng, Zhongyu Sun, Yichun Xie, Long Yang, Zhihui Wang and Philip T. Eubank. Their work appears in journals such as AIChE Journal, Neural Computing and Applications, Journal of Plant Ecology, IEEE Transactions on Intelligent Transportation Systems and IEEE Transactions on Cybernetics.

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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