Sun‐Yuan Kung
About
In The Last Decade
Sun‐Yuan Kung
352 papers receiving 10.3k citations
Hit Papers
Peers
Comparison fields: 5 of 185
- Electrical and Electronic Engineering 2.6k
- Computer Vision and Pattern Recognition 2.3k
- Signal Processing 2.3k
- Computer Networks and Communications 2.2k
- Artificial Intelligence 2.1k
Countries citing papers authored by Sun‐Yuan Kung
This map shows the geographic impact of Sun‐Yuan Kung'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 Sun‐Yuan Kung with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sun‐Yuan Kung more than expected).
Fields of papers citing papers by Sun‐Yuan Kung
This network shows the impact of papers produced by Sun‐Yuan Kung. 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 Sun‐Yuan Kung. The network helps show where Sun‐Yuan Kung may publish in the future.
Co-authorship network of co-authors of Sun‐Yuan Kung
This figure shows the co-authorship network connecting the top 25 collaborators of Sun‐Yuan Kung. A scholar is included among the top collaborators of Sun‐Yuan Kung 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 Sun‐Yuan Kung. Sun‐Yuan Kung is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 3 | |
| 3 | 3 | |
| 4 | 6 | |
| 5 | 3 | |
| 6 | 7 | |
| 7 | 12 | |
| 8 | 10 | |
| 9 | 24 | |
| 10 | 24 | |
| 11 | 32 | |
| 12 | 12 | |
| 13 | 43 | |
| 14 | 40 | |
| 15 | 38 | |
| 16 | 14 | |
| 17 | From green computing to big-data learning: A kernel learning perspective. | 1 |
| 18 | 0 | |
| 19 | TIMING ANALYSIS AND DESIGN OPTIMIZATION OF VLSI DATA FLOW ARRAYS. | 9 |
| 20 | 23 |
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.