Ming Liu
Impact in
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- Robotic Path Planning Algorithms
- Advanced Neural Network Applications
- Advanced Vision and Imaging
- Advanced Image and Video Retrieval Techniques
- Geology top 0.5%
- 3D Surveying and Cultural Heritage
Papers in
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- Advanced Vision and Imaging 70
- Advanced Neural Network Applications 49
- Robotic Path Planning Algorithms 42
- Advanced Image and Video Retrieval Techniques 35
- Video Surveillance and Tracking Methods 29
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- Robotics and Sensor-Based Localization 121
- Journals
- IEEE Robotics and Automation Letters (28 papers)IEEE Transactions on Automation Science and Engineering (16 papers)IEEE/ASME Transactions on Mechatronics (8 papers)IEEE Transactions on Intelligent Transportation Systems (8 papers)IEEE Transactions on Cybernetics (7 papers)
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Ming Liu
416 papers receiving 8.8k citations
Hit Papers
Peers
Comparison fields: 5 of 185
- Computer Vision and Pattern Recognition 4.3k
- Geology 703
- Aerospace Engineering 3.0k
- Automotive Engineering 814
- Artificial Intelligence 1.8k
Countries citing papers authored by Ming Liu
This map shows the geographic impact of Ming Liu'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 Ming Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming Liu more than expected).
Fields of papers citing papers by Ming Liu
This network shows the impact of papers produced by Ming Liu. 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 Ming Liu. The network helps show where Ming Liu may publish in the future.
Co-authors
The 25 scholars most cited alongside Ming Liu, 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 | 6 | |
| 2 | 2024 | 11 | |
| 3 | 2024 | 13 | |
| 4 | 2024 | 14 | |
| 5 | 2024 | 4 | |
| 6 | 2024 | 2 | |
| 7 | 2024 | 3 | |
| 8 | 2024 | 9 | |
| 9 | 2024 | 3 | |
| 10 | 2023 | 1 | |
| 11 | 2023 | 1 | |
| 12 | 2023 | 2 | |
| 13 | 2023 | 28 | |
| 14 | 2023 | 5 | |
| 15 | 2021 | 30 | |
| 16 | 2021 | 56 | |
| 17 | 2020 | 21 | |
| 18 | 2020 | 18 | |
| 19 | 2019 | 3 | |
| 20 | 2019 | 147 |
About Ming Liu
Ming Liu is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Geology, Automotive Engineering and Control and Systems Engineering, having authored 452 papers that have together received 9.0k indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (121 papers), Advanced Vision and Imaging (70 papers), Advanced Neural Network Applications (49 papers), Robotic Path Planning Algorithms (42 papers), Autonomous Vehicle Technology and Safety (36 papers), Advanced Image and Video Retrieval Techniques (35 papers), Indoor and Outdoor Localization Technologies (31 papers) and Video Surveillance and Tracking Methods (29 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (4.3k citations), Geology (703 citations), Aerospace Engineering (3.0k citations), Automotive Engineering (814 citations) and Artificial Intelligence (1.8k citations). Ming Liu has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Yuxiang Sun, Lei Tai, Roland Siegwart, Max Q.‐H. Meng, Lujia Wang, Giuseppe Paolo, Weixun Zuo, Rui Fan, Hengli Wang and François Pomerleau. Their work appears in journals such as IEEE Robotics and Automation Letters, IEEE Transactions on Automation Science and Engineering, IEEE/ASME Transactions on Mechatronics, IEEE Transactions on Intelligent Transportation Systems and IEEE Transactions on Cybernetics.
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.