Yaxiong Wang
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- Advanced Image and Video Retrieval Techniques 11
- Multimodal Machine Learning Applications 7
- Video Surveillance and Tracking Methods 6
- Image Retrieval and Classification Techniques 5
- Advanced Neural Network Applications 3
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- Advanced Thermodynamics and Statistical Mechanics 6
- Mechanical Engineering top 10%
- Thermodynamic and Exergetic Analyses of Power and Cooling Systems 9
- Advanced Thermodynamic Systems and Engines 5
- Cited by
- Computer Vision and Pattern RecognitionEnergy Engineering and Power TechnologyStatistical and Nonlinear Physics
- Journals
- IEEE Transactions on Image Processing (3 papers)Energy Conversion and Management (2 papers)Energy (2 papers)
- Partner nations
- ChinaAustraliaUnited Kingdom
In The Last Decade
Yaxiong Wang
28 papers receiving 571 citations
Peers
Comparison fields: 5 of 70
- Computer Vision and Pattern Recognition 221
- Energy Engineering and Power Technology 26
- Statistical and Nonlinear Physics 96
- Renewable Energy, Sustainability and the Environment 106
- Mechanical Engineering 242
Countries citing papers authored by Yaxiong Wang
This map shows the geographic impact of Yaxiong 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 Yaxiong Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yaxiong Wang more than expected).
Fields of papers citing papers by Yaxiong Wang
This network shows the impact of papers produced by Yaxiong 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 Yaxiong Wang. The network helps show where Yaxiong Wang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Yaxiong 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 | 2025 | 1 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 3 | |
| 5 | 2023 | 2 | |
| 6 | 2023 | 23 | |
| 7 | 2023 | 10 | |
| 8 | 2021 | 17 | |
| 9 | 2021 | 31 | |
| 10 | 2021 | 2 | |
| 11 | 2021 | 3 | |
| 12 | 2021 | 34 | |
| 13 | 2021 | 13 | |
| 14 | 2020 | 2 | |
| 15 | 2020 | 39 | |
| 16 | 2020 | 11 | |
| 17 | 2020 | 18 | |
| 18 | 2019 | 38 | |
| 19 | 2017 | 15 | |
| 20 | 2017 | 33 |
About Yaxiong Wang
Yaxiong Wang is a scholar working on Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics and Computer Graphics and Computer-Aided Design, having authored 31 papers that have together received 584 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (11 papers), Thermodynamic and Exergetic Analyses of Power and Cooling Systems (9 papers), Multimodal Machine Learning Applications (7 papers), Advanced Thermodynamics and Statistical Mechanics (6 papers), Video Surveillance and Tracking Methods (6 papers), Advanced Thermodynamic Systems and Engines (5 papers), Image Retrieval and Classification Techniques (5 papers) and Advanced Neural Network Applications (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (221 citations), Energy Engineering and Power Technology (26 citations) and Statistical and Nonlinear Physics (96 citations). Yaxiong Wang has collaborated with scholars based in China, Australia and United Kingdom. Frequent co-authors include Jiangfeng Wang, Li Zhu, Xueming Qian, Christos N. Markides, Jian Song, Kai Wang, Yiping Dai, Pan Zhao, Ziyang Cheng and Zhedong Zheng. Their work appears in journals such as IEEE Transactions on Image Processing, Energy Conversion and Management and Energy.
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.