Seng Keat Gan
- Computer Vision and Pattern Recognition top 5%
- Aerospace Engineering top 5%
- Computer Networks and Communications top 10%
- Control and Systems Engineering top 10%
- Artificial Intelligence
- Co-authors
- Salah SukkariehKwangjin YangEva Besada-PortasGonzalo PájaresPablo LanillosRobert FitchChi‐Hwa WangXin Hao Zhu
- Topics
- UAV Applications and Optimization (6 papers)Robotic Path Planning Algorithms (6 papers)Distributed Control Multi-Agent Systems (5 papers)
- Cited by
- Computer Vision and Pattern RecognitionAerospace EngineeringComputer Networks and Communications
- Partner nations
- AustraliaSouth KoreaSingapore
In The Last Decade
Seng Keat Gan
10 papers receiving 407 citations
Peers
Comparison fields: 5 of 57
- Computer Vision and Pattern Recognition 258
- Aerospace Engineering 230
- Computer Networks and Communications 138
- Control and Systems Engineering 88
- Artificial Intelligence 73
Countries citing papers authored by Seng Keat Gan
This map shows the geographic impact of Seng Keat Gan'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 Seng Keat Gan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Seng Keat Gan more than expected).
Fields of papers citing papers by Seng Keat Gan
This network shows the impact of papers produced by Seng Keat Gan. 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 Seng Keat Gan. The network helps show where Seng Keat Gan may publish in the future.
Co-authorship network of co-authors of Seng Keat Gan
This figure shows the co-authorship network connecting the top 25 collaborators of Seng Keat Gan. A scholar is included among the top collaborators of Seng Keat Gan 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 Seng Keat Gan. Seng Keat Gan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 11 | |
| 2 | 75 | |
| 3 | 22 | |
| 4 | 8 | |
| 5 | 105 | |
| 6 | 18 | |
| 7 | 56 | |
| 8 | 83 | |
| 9 | 3D Path Planning for a Rotary Wing UAV using a Gaussian Process O ccupancy Map | 8 |
| 10 | 32 |
About Seng Keat Gan
Seng Keat Gan is a scholar working on Aerospace Engineering, Computer Vision and Pattern Recognition and Computer Networks and Communications, having authored 10 papers that have together received 418 indexed citations. Recurring topics across this work include UAV Applications and Optimization (6 papers), Robotic Path Planning Algorithms (6 papers) and Distributed Control Multi-Agent Systems (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (258 citations), Aerospace Engineering (230 citations) and Computer Networks and Communications (138 citations). Seng Keat Gan has collaborated with scholars based in Australia, South Korea and Singapore. Frequent co-authors include Salah Sukkarieh, Kwangjin Yang, Eva Besada-Portas, Gonzalo Pájares, Pablo Lanillos, Robert Fitch, Chi‐Hwa Wang, Xin Hao Zhu, Yen Wah Tong and David Hyunchul Shim. Their work appears in journals such as Information Sciences, Journal of Biomedical Materials Research Part A and Autonomous Robots.
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.