Yun Du
- Computer Vision and Pattern Recognition top 5%
- Aerospace Engineering top 5%
- Mechanical Engineering
- Electrical and Electronic Engineering
- Automotive Engineering top 5%
- Co-authors
- Shikai ShaoPeng YuChenglong HeRen-Kae ShiueChaohua DaiLi Fei-FeiC. S. ChangHsin-Yi Chuang
- Topics
- Robotic Path Planning Algorithms (6 papers)Advanced Algorithms and Applications (5 papers)Advanced Sensor and Control Systems (4 papers)
- Partner nations
- ChinaUnited KingdomTaiwan
In The Last Decade
Yun Du
24 papers receiving 621 citations
Hit Papers
Peers
Comparison fields: 5 of 65
- Computer Vision and Pattern Recognition 272
- Aerospace Engineering 203
- Mechanical Engineering 154
- Electrical and Electronic Engineering 144
- Automotive Engineering 139
Countries citing papers authored by Yun Du
This map shows the geographic impact of Yun Du'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 Yun Du with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yun Du more than expected).
Fields of papers citing papers by Yun Du
This network shows the impact of papers produced by Yun Du. 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 Yun Du. The network helps show where Yun Du may publish in the future.
Co-authorship network of co-authors of Yun Du
This figure shows the co-authorship network connecting the top 25 collaborators of Yun Du. A scholar is included among the top collaborators of Yun Du 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 Yun Du. Yun Du is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 9 | |
| 6 | 17 | |
| 7 | 73 | |
| 8 | 124 | |
| 9 | Efficient path planning for UAV formation via comprehensively improved particle swarm optimizationbreakdown → | 260 |
| 10 | 3 | |
| 11 | 1 | |
| 12 | Design and application of intelligent control system for greenhouse environment based on CAN bus | 3 |
| 13 | 2 | |
| 14 | Progresses in study of pipeline robot | 7 |
| 15 | 4 | |
| 16 | 3 | |
| 17 | 4 | |
| 18 | 1 | |
| 19 | 1 | |
| 20 | 58 |
About Yun Du
Yun Du is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition and Process Chemistry and Technology, having authored 29 papers that have together received 639 indexed citations. Recurring topics across this work include Robotic Path Planning Algorithms (6 papers), Advanced Algorithms and Applications (5 papers) and Advanced Sensor and Control Systems (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (272 citations), Automotive Engineering (139 citations) and Aerospace Engineering (203 citations). Yun Du has collaborated with scholars based in China, United Kingdom and Taiwan. Frequent co-authors include Shikai Shao, Peng Yu, Chenglong He, Ren-Kae Shiue, Chaohua Dai, Li Fei-Fei, C. S. Chang, Hsin-Yi Chuang, F. Li and Quanmin Zhu. Their work appears in journals such as Journal of Power Sources, Scientific Reports and Materials Science and Engineering A.
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.