Peide Cai
Impact in
- Automotive Engineering top 5%
- Autonomous Vehicle Technology and Safety
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- Advanced Neural Network Applications
- Video Surveillance and Tracking Methods
- Robotic Path Planning Algorithms
- Advanced Vision and Imaging
Papers in
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- Autonomous Vehicle Technology and Safety 10
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- Advanced Neural Network Applications 5
- Robotic Path Planning Algorithms 3
- Video Surveillance and Tracking Methods 2
- Advanced Vision and Imaging 2
- Co-authors
- Ming Liu (10 shared papers)Hengli Wang (8 shared papers)Yuxiang Sun (6 shared papers)Rui Fan (4 shared papers)Huaiyang Huang (2 shared papers)Lujia Wang (4 shared papers)Yuxuan Liu (1 shared paper)Ming Liu (1 shared paper)
- Journals
- IEEE Robotics and Automation Letters (3 papers)IEEE/ASME Transactions on Mechatronics (1 paper)IEEE Transactions on Intelligent Transportation Systems (1 paper)Rare & Special e-Zone (The Hong Kong University of Science and Technology) (3 papers)2022 International Conference on Robotics and Automation (ICRA) (2 papers)
- Partner nations
- Hong KongChinaUnited States
In The Last Decade
Peide Cai
12 papers receiving 316 citations
Peers
Comparison fields: 5 of 44
- Automotive Engineering 148
- Computer Vision and Pattern Recognition 195
- Media Technology 22
- Control and Systems Engineering 57
- Instrumentation 8
Countries citing papers authored by Peide Cai
This map shows the geographic impact of Peide Cai'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 Peide Cai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peide Cai more than expected).
Fields of papers citing papers by Peide Cai
This network shows the impact of papers produced by Peide Cai. 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 Peide Cai. The network helps show where Peide Cai may publish in the future.
Co-authors
The 14 scholars most cited alongside Peide Cai, 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 | 2021 | 56 | |
| 2 | 2021 | 46 | |
| 3 | 2021 | 41 | |
| 4 | 2022 | 36 | |
| 5 | 2019 | 36 | |
| 6 | 2021 | 30 | |
| 7 | 2020 | 24 | |
| 8 | 2021 | 20 | |
| 9 | 2022 | 17 | |
| 10 | 2021 | 8 | |
| 11 | 2021 | 8 | |
| 12 | 2022 | 4 |
About Peide Cai
Peide Cai is a scholar working on Automotive Engineering, Computer Vision and Pattern Recognition, Artificial Intelligence, Control and Systems Engineering and Civil and Structural Engineering, having authored 12 papers that have together received 326 indexed citations. Recurring topics across this work include Autonomous Vehicle Technology and Safety (10 papers), Advanced Neural Network Applications (5 papers), Robotic Path Planning Algorithms (3 papers), Video Surveillance and Tracking Methods (2 papers), Reinforcement Learning in Robotics (2 papers), Advanced Vision and Imaging (2 papers), Traffic control and management (2 papers) and 3D Shape Modeling and Analysis (1 paper). The work is most often cited by research in Automotive Engineering (148 citations), Computer Vision and Pattern Recognition (195 citations), Media Technology (22 citations), Control and Systems Engineering (57 citations) and Instrumentation (8 citations). Peide Cai has collaborated with scholars based in Hong Kong, China and United States. Frequent co-authors include Ming Liu, Hengli Wang, Yuxiang Sun, Rui Fan, Huaiyang Huang, Lujia Wang, Yuxuan Liu, Ming Liu, Yuying Chen and Jin Wu. Their work appears in journals such as IEEE Robotics and Automation Letters, IEEE/ASME Transactions on Mechatronics, IEEE Transactions on Intelligent Transportation Systems, Rare & Special e-Zone (The Hong Kong University of Science and Technology) and 2022 International Conference on Robotics and Automation (ICRA).
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.