Chenyu Wang
Impact in
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- Advanced Neural Network Applications
- Medical Image Segmentation Techniques
- Mechanical Engineering top 10%
- Innovative Energy Harvesting Technologies
Papers in
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- Advanced Neural Network Applications 2
- Face recognition and analysis 2
- Advanced Steganography and Watermarking Techniques 1
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- Innovative Energy Harvesting Technologies 3
- Co-authors
- Chen Chen (3 shared papers)Shaohua Wan (2 shared papers)Ci He (1 shared paper)Cong Li (1 shared paper)Kangqi Fan (3 shared papers)Fei Wang (3 shared papers)Weidong Wang (1 shared paper)Yan Zhang (1 shared paper)
In The Last Decade
Chenyu Wang
9 papers receiving 335 citations
Chenyu Wang's Hit Papers
Peers
Comparison fields: 5 of 26
- Computer Vision and Pattern Recognition 81
- Mechanical Engineering 106
- Computer Networks and Communications 24
- Automotive Engineering 9
- Media Technology 4
Countries citing papers authored by Chenyu Wang
This map shows the geographic impact of Chenyu 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 Chenyu Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chenyu Wang more than expected).
Fields of papers citing papers by Chenyu Wang
This network shows the impact of papers produced by Chenyu 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 Chenyu Wang. The network helps show where Chenyu Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Chenyu Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Edge Intelligence Empowered Vehicle Detection and Image Segmentation for Autonomous Vehicles Hit paper breakdown → | 2023 | 155 |
| 2 | 2021 | 62 | |
| 3 | 2021 | 45 | |
| 4 | 2023 | 34 | |
| 5 | 2022 | 26 | |
| 6 | 2023 | 13 | |
| 7 | 2015 | 2 | |
| 8 | 2014 | 1 | |
| 9 | 2020 | 1 | |
| 10 | 2022 | 1 | |
| 11 | 2024 | 0 | |
| 12 | 2025 | 0 | |
| 13 | 2025 | 0 |
About Chenyu Wang
Chenyu Wang is a scholar working on Computer Vision and Pattern Recognition, Mechanical Engineering, Electrical and Electronic Engineering, Nuclear Energy and Engineering and Waste Management and Disposal, having authored 13 papers that have together received 340 indexed citations. Recurring topics across this work include Innovative Energy Harvesting Technologies (3 papers), Advanced Neural Network Applications (2 papers), Face recognition and analysis (2 papers), Vehicular Ad Hoc Networks (VANETs) (1 paper), Silicon Carbide Semiconductor Technologies (1 paper) and Advanced Steganography and Watermarking Techniques (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (81 citations), Mechanical Engineering (106 citations), Computer Networks and Communications (24 citations), Automotive Engineering (9 citations) and Media Technology (4 citations). Chenyu Wang has collaborated with scholars based in China, Australia and Sweden. Frequent co-authors include Chen Chen, Shaohua Wan, Ci He, Cong Li, Kangqi Fan, Fei Wang, Weidong Wang, Yan Zhang, Peihong Wang and Ming Bo Xiao. Their work appears in journals such as Renewable Energy, Energy Conversion and Management, IEEE Transactions on Intelligent Transportation Systems, Digital Communications and Networks and Chinese Journal of Electronics.
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.