Eric Wang

30 papers receiving 370 citations

Peers

Eric Wang
Comparison fields: 5 of 73
  • Energy Engineering and Power Technology 13
  • Computer Vision and Pattern Recognition 88
  • Environmental Engineering 50
  • Media Technology 21
  • Control and Systems Engineering 51
Replace Kehua Li with:
Kehua Li China
Xiaodi Zhang China
Stéphane Thil France
Lihua Hu China
Michael Lichtenstern Germany
Agnieszka E. Piotrowska Poland
Branislav M. Todorović Serbia
Qing Song United States
Lijuan Zhu China
Eric Wang relative to Kehua Li China Kehua Li's profile →
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Citations per year

Countries citing papers authored by Eric Wang

Since Specialization
Citations

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

Fields of papers citing papers by Eric Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010100
2 201858
3 202150
4 201837
5 201915
6 201814
7 201814
8 201713
9 202411
10 20228
11 20128
12 20207
13 20167
14 20246
15 20115
16 20114
17 20184
18 20094
19 20114
20 20233

About Eric Wang

Eric Wang is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Artificial Intelligence, Control and Systems Engineering and Computer Networks and Communications, having authored 33 papers that have together received 388 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (5 papers), Video Coding and Compression Technologies (3 papers), Astro and Planetary Science (3 papers), Advanced Image Processing Techniques (3 papers), Geomagnetism and Paleomagnetism Studies (3 papers), Smart Grid Security and Resilience (3 papers), Smart Grid Energy Management (3 papers) and Image Enhancement Techniques (3 papers). The work is most often cited by research in Energy Engineering and Power Technology (13 citations), Computer Vision and Pattern Recognition (88 citations), Environmental Engineering (50 citations), Media Technology (21 citations) and Control and Systems Engineering (51 citations). Eric Wang has collaborated with scholars based in Australia, United States and China. Frequent co-authors include Wei Xiang, Shyi-Min Lu, Falin Chen, Si‐Chen Lee, Kang Han, Md. Masud Rana, Xuehua Li, Tao Huang, Bong Jun Choi and Allan Lee. Their work appears in journals such as IEEE Access, Multimedia Tools and Applications, IEEE Internet of Things Journal, IEEE Transactions on Geoscience and Remote Sensing 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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