King Sun Fu
- Control and Systems Engineering top 1%
- Computer Vision and Pattern Recognition top 1%
- Artificial Intelligence top 2%
- Biomedical Engineering top 10%
- Mechanical Engineering top 10%
- Topics
- Algorithms and Data Compression (3 papers)semigroups and automata theory (2 papers)Logic, programming, and type systems (1 paper)
- Cited by
- Control and Systems EngineeringComputer Vision and Pattern RecognitionArtificial Intelligence
- Journals
- IEEE Transactions on ComputersIEEE Transactions on Systems Man and CyberneticsCERN Document Server (European Organization for Nuclear Research)
- Partner nations
- United StatesFranceChina
In The Last Decade
King Sun Fu
12 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 135
- Control and Systems Engineering 850
- Computer Vision and Pattern Recognition 700
- Artificial Intelligence 634
- Biomedical Engineering 311
- Mechanical Engineering 298
Countries citing papers authored by King Sun Fu
This map shows the geographic impact of King Sun Fu'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 King Sun Fu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites King Sun Fu more than expected).
Fields of papers citing papers by King Sun Fu
This network shows the impact of papers produced by King Sun Fu. 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 King Sun Fu. The network helps show where King Sun Fu may publish in the future.
Co-authorship network of co-authors of King Sun Fu
This figure shows the co-authorship network connecting the top 25 collaborators of King Sun Fu. A scholar is included among the top collaborators of King Sun Fu 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 King Sun Fu. King Sun Fu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Applications of Pattern Recognition | 15 |
| 2 | Robotics: Control, Sensing, Vision, and Intelligencebreakdown → | 1140 |
| 3 | Tutorial on robotics | 33 |
| 4 | 8 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 81 | |
| 8 | 112 | |
| 9 | Statistical Pattern Classification Using Contextual Information | 22 |
| 10 | 149 | |
| 11 | Stochastic syntactic analysis and syntactic pattern recognition | 3 |
| 12 | Syntactic pattern recognition and applicationsbreakdown → | 646 |
About King Sun Fu
King Sun Fu is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 12 papers that have together received 2.2k indexed citations. Recurring topics across this work include Algorithms and Data Compression (3 papers), semigroups and automata theory (2 papers) and Logic, programming, and type systems (1 paper). The work is most often cited by research in Control and Systems Engineering (850 citations), Computer Vision and Pattern Recognition (700 citations) and Artificial Intelligence (634 citations). King Sun Fu has collaborated with scholars based in United States, France and China. Frequent co-authors include Rafael C. González, Shin-Yee Lu, L. F. Pau, Josef Kittler, Tian Huang and Tanaka. Their work appears in journals such as IEEE Transactions on Computers, IEEE Transactions on Systems Man and Cybernetics and CERN Document Server (European Organization for Nuclear Research).
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.