Tongyi Cao
- Computer Vision and Pattern Recognition top 5%
- Automotive Engineering top 5%
- Aerospace Engineering top 10%
- Computational Mechanics top 10%
- Environmental Engineering
- Co-authors
- Maosheng YeShuangjie XuQifeng ChenXiaoyi ZouKe XuHaim SchweitzerTengfei WangDit‐Yan Yeung
- Topics
- Remote Sensing and LiDAR Applications (3 papers)Robotics and Sensor-Based Localization (3 papers)Autonomous Vehicle Technology and Safety (2 papers)
- Journals
- 2021 IEEE/CVF International Conference on Computer Vision (ICCV)Rare & Special e-Zone (The Hong Kong University of Science and Technology)arXiv (Cornell University)
- Partner nations
- Hong KongUnited StatesChina
In The Last Decade
Tongyi Cao
9 papers receiving 349 citations
Peers
Comparison fields: 5 of 41
- Computer Vision and Pattern Recognition 234
- Automotive Engineering 129
- Aerospace Engineering 99
- Computational Mechanics 68
- Environmental Engineering 65
Countries citing papers authored by Tongyi Cao
This map shows the geographic impact of Tongyi Cao'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 Tongyi Cao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tongyi Cao more than expected).
Fields of papers citing papers by Tongyi Cao
This network shows the impact of papers produced by Tongyi Cao. 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 Tongyi Cao. The network helps show where Tongyi Cao may publish in the future.
Co-authorship network of co-authors of Tongyi Cao
This figure shows the co-authorship network connecting the top 25 collaborators of Tongyi Cao. A scholar is included among the top collaborators of Tongyi Cao based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Tongyi Cao. Tongyi Cao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 10 | |
| 2 | 3 | |
| 3 | 25 | |
| 4 | 35 | |
| 5 | 116 | |
| 6 | Provably adaptive reinforcement learning in metric spaces | 1 |
| 7 | 155 | |
| 8 | Disagreement-based combinatorial pure exploration: Efficient algorithms and an analysis with localization | 1 |
| 9 | 13 |
About Tongyi Cao
Tongyi Cao is a scholar working on Environmental Engineering, Computer Vision and Pattern Recognition and Geology, having authored 9 papers that have together received 359 indexed citations. Recurring topics across this work include Remote Sensing and LiDAR Applications (3 papers), Robotics and Sensor-Based Localization (3 papers) and Autonomous Vehicle Technology and Safety (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (234 citations), Automotive Engineering (129 citations) and Geology (54 citations). Tongyi Cao has collaborated with scholars based in Hong Kong, United States and China. Frequent co-authors include Maosheng Ye, Shuangjie Xu, Qifeng Chen, Xiaoyi Zou, Ke Xu, Haim Schweitzer, Tengfei Wang, Dit‐Yan Yeung, Fang Lü and Akshay Krishnamurthy. Their work appears in journals such as 2021 IEEE/CVF International Conference on Computer Vision (ICCV), Rare & Special e-Zone (The Hong Kong University of Science and Technology) and arXiv (Cornell University).
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.