Ao Wang
Impact in
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- Advanced Neural Network Applications
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- Seismic Waves and Analysis
- Seismic Imaging and Inversion Techniques
Papers in
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- Remote Sensing and LiDAR Applications 4
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- Multimodal Machine Learning Applications 1
- Co-authors
- Hui Chen (3 shared papers)Guiguang Ding (3 shared papers)Zijia Lin (3 shared papers)Jungong Han (2 shared papers)Shuo Shi (6 shared papers)Chao Shen (3 shared papers)Lin Du (3 shared papers)Wei Gong (3 shared papers)
- Journals
- IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (3 papers)Remote Sensing (1 paper)Urban forestry & urban greening (1 paper)The Photogrammetric Record (1 paper)IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)
- Partner nations
- ChinaGermanyUnited Kingdom
In The Last Decade
Ao Wang
15 papers receiving 359 citations
Ao Wang's Hit Papers
Peers
Comparison fields: 5 of 75
- Computer Vision and Pattern Recognition 107
- Geophysics 61
- Environmental Engineering 57
- Ocean Engineering 61
- Media Technology 24
Countries citing papers authored by Ao Wang
This map shows the geographic impact of Ao 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 Ao Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ao Wang more than expected).
Fields of papers citing papers by Ao Wang
This network shows the impact of papers produced by Ao 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 Ao Wang. The network helps show where Ao Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Ao 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 | Rep ViT: Revisiting Mobile CNN From ViT Perspective Hit paper breakdown → | 2024 | 201 |
| 2 | 2022 | 40 | |
| 3 | 2024 | 29 | |
| 4 | 2015 | 28 | |
| 5 | 2016 | 26 | |
| 6 | 2019 | 20 | |
| 7 | 2023 | 5 | |
| 8 | 2024 | 4 | |
| 9 | 2024 | 3 | |
| 10 | 2021 | 3 | |
| 11 | 2023 | 2 | |
| 12 | 2010 | 2 | |
| 13 | 2025 | 1 | |
| 14 | Prediction of Land Subsidence of Soft Soil in Foshan City with GMS | 2009 | 1 |
| 15 | 2025 | 1 | |
| 16 | 2024 | 0 |
About Ao Wang
Ao Wang is a scholar working on Environmental Engineering, Computer Vision and Pattern Recognition, Ecology, Ocean Engineering and Artificial Intelligence, having authored 16 papers that have together received 366 indexed citations. Recurring topics across this work include Remote Sensing and LiDAR Applications (4 papers), Remote Sensing in Agriculture (3 papers), Seismic Waves and Analysis (2 papers), Seismic Imaging and Inversion Techniques (2 papers), Methane Hydrates and Related Phenomena (2 papers), Geophysics and Sensor Technology (2 papers), COVID-19 diagnosis using AI (1 paper) and Multimodal Machine Learning Applications (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (107 citations), Geophysics (61 citations), Environmental Engineering (57 citations), Ocean Engineering (61 citations) and Media Technology (24 citations). Ao Wang has collaborated with scholars based in China, Germany and United Kingdom. Frequent co-authors include Hui Chen, Guiguang Ding, Zijia Lin, Jungong Han, Shuo Shi, Chao Shen, Lin Du, Wei Gong, Limin Wang and Feng Cheng. Their work appears in journals such as IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Remote Sensing, Urban forestry & urban greening, The Photogrammetric Record 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.