Teng Ran
Impact in
- Geology top 10%
- 3D Surveying and Cultural Heritage
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- Robotic Path Planning Algorithms
- Advanced Image and Video Retrieval Techniques
- Video Surveillance and Tracking Methods
Papers in
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- Advanced Image and Video Retrieval Techniques 10
- Robotic Path Planning Algorithms 4
- Advanced Neural Network Applications 3
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- Robotics and Sensor-Based Localization 14
- Co-authors
- Liang Yuan (22 shared papers)Li He (11 shared papers)Qing Tao (5 shared papers)Zhizhou Wu (2 shared papers)Jie Mei (1 shared paper)Ran Huang (1 shared paper)Guoquan Zheng (2 shared papers)Li He (1 shared paper)
- Journals
- Displays (5 papers)Computers & Graphics (3 papers)IEEE Sensors Journal (3 papers)IEEE Transactions on Instrumentation and Measurement (2 papers)Nonlinear Dynamics (2 papers)
- Partner nations
- China
In The Last Decade
Teng Ran
23 papers receiving 289 citations
Peers
Comparison fields: 5 of 43
- Geology 53
- Computer Vision and Pattern Recognition 184
- Aerospace Engineering 163
- Automotive Engineering 34
- Control and Systems Engineering 49
Countries citing papers authored by Teng Ran
This map shows the geographic impact of Teng Ran'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 Teng Ran with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Teng Ran more than expected).
Fields of papers citing papers by Teng Ran
This network shows the impact of papers produced by Teng Ran. 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 Teng Ran. The network helps show where Teng Ran may publish in the future.
Co-authors
The 21 scholars most cited alongside Teng Ran, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 80 | |
| 2 | 2020 | 50 | |
| 3 | 2022 | 26 | |
| 4 | 2021 | 18 | |
| 5 | 2023 | 16 | |
| 6 | 2021 | 13 | |
| 7 | 2023 | 11 | |
| 8 | 2021 | 11 | |
| 9 | 2022 | 10 | |
| 10 | 2024 | 10 | |
| 11 | 2022 | 9 | |
| 12 | 2023 | 6 | |
| 13 | 2024 | 6 | |
| 14 | 2023 | 5 | |
| 15 | 2024 | 5 | |
| 16 | 2024 | 5 | |
| 17 | 2022 | 5 | |
| 18 | 2023 | 2 | |
| 19 | 2025 | 1 | |
| 20 | 2024 | 1 |
About Teng Ran
Teng Ran is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Artificial Intelligence, Geology and Automotive Engineering, having authored 28 papers that have together received 293 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (14 papers), Advanced Image and Video Retrieval Techniques (10 papers), 3D Surveying and Cultural Heritage (5 papers), Autonomous Vehicle Technology and Safety (4 papers), Robotic Path Planning Algorithms (4 papers), Reinforcement Learning in Robotics (4 papers), Indoor and Outdoor Localization Technologies (4 papers) and Advanced Neural Network Applications (3 papers). The work is most often cited by research in Geology (53 citations), Computer Vision and Pattern Recognition (184 citations), Aerospace Engineering (163 citations), Automotive Engineering (34 citations) and Control and Systems Engineering (49 citations). Teng Ran has collaborated with scholars based in China. Frequent co-authors include Liang Yuan, Li He, Qing Tao, Zhizhou Wu, Jie Mei, Ran Huang, Guoquan Zheng, Li He, Jun Zhao and Yadong Wang. Their work appears in journals such as Displays, Computers & Graphics, IEEE Sensors Journal, IEEE Transactions on Instrumentation and Measurement and Nonlinear Dynamics.
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.