Xiaonan Wang

635 citations
17 papers · 221 · h-index 8

Impact in

Papers in

Xiaonan Wang

14 papers receiving 218 citations

Peers

Xiaonan Wang
Comparison fields: 5 of 51
  • Industrial and Manufacturing Engineering 76
  • Computer Vision and Pattern Recognition 64
  • Polymers and Plastics 32
  • Electrical and Electronic Engineering 84
  • Civil and Structural Engineering 28
Replace Georgiy Yaskov with:
Georgiy Yaskov Ukraine
Keheng Zhu China
Ramya Maranan India
Alexey Fomin Russia
Xiaogang Jia China
Xuzhu Dong China
Patience E. Orukpe Nigeria
Xun Dong China
Zhiyin Chen China
Joon Sik Son South Korea
Xiaonan Wang relative to Georgiy Yaskov Ukraine Georgiy Yaskov's profile →
Citations per field
00.5×10×17×
Georgiy Yaskov · 1×
Citations per year

Countries citing papers authored by Xiaonan Wang

Since Specialization
Citations

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

Fields of papers citing papers by Xiaonan Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

17 of 17 papers shown
#Work
1 201882
2 202445
3 202224
4 202518
5 202214
6 202210
7 201610
8 20258
9 20194
10 20242
11 20111
12 20251
13 20171
14 20161
15 20260
16 20250
17 20250

About Xiaonan Wang

Xiaonan Wang is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Materials Chemistry, Artificial Intelligence and Aerospace Engineering, having authored 17 papers that have together received 221 indexed citations. Recurring topics across this work include Perovskite Materials and Applications (7 papers), Video Surveillance and Tracking Methods (3 papers), Conducting polymers and applications (2 papers), Quantum Dots Synthesis And Properties (2 papers), Advanced Neural Network Applications (2 papers), Chalcogenide Semiconductor Thin Films (2 papers), Industrial Vision Systems and Defect Detection (2 papers) and Advanced Image and Video Retrieval Techniques (2 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (76 citations), Computer Vision and Pattern Recognition (64 citations), Polymers and Plastics (32 citations), Electrical and Electronic Engineering (84 citations) and Civil and Structural Engineering (28 citations). Xiaonan Wang has collaborated with scholars based in China, Türkiye and Japan. Frequent co-authors include Kui Yuan, Yue Guo, Yibin Huang, Hao Hu, Libing Yao, Jingjing Xue, Rui Wang, Shaochen Zhang, Jiazhe Xu and Caner Değer. Their work appears in journals such as ACS Energy Letters, Archives of Computational Methods in Engineering, Carbon Energy, Advanced Materials and Expert Systems with Applications.

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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