Shiliang Sun
- Artificial Intelligence top 0.2%
- Computer Vision and Pattern Recognition top 0.2%
- Signal Processing top 1%
- Media Technology top 0.5%
- Cognitive Neuroscience top 5%
- Topics
- Face and Expression Recognition (47 papers)Domain Adaptation and Few-Shot Learning (37 papers)Text and Document Classification Technologies (23 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceJournal of The Electrochemical SocietyIEEE Transactions on Image Processing
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Shiliang Sun
185 papers receiving 7.0k citations
Hit Papers
Peers
Comparison fields: 5 of 186
- Artificial Intelligence 3.7k
- Computer Vision and Pattern Recognition 2.7k
- Signal Processing 747
- Media Technology 598
- Cognitive Neuroscience 582
Countries citing papers authored by Shiliang Sun
This map shows the geographic impact of Shiliang Sun'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 Shiliang Sun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shiliang Sun more than expected).
Fields of papers citing papers by Shiliang Sun
This network shows the impact of papers produced by Shiliang Sun. 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 Shiliang Sun. The network helps show where Shiliang Sun may publish in the future.
Co-authorship network of co-authors of Shiliang Sun
This figure shows the co-authorship network connecting the top 25 collaborators of Shiliang Sun. A scholar is included among the top collaborators of Shiliang Sun 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 Shiliang Sun. Shiliang Sun is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 3 | |
| 3 | 1 | |
| 4 | 21 | |
| 5 | 3 | |
| 6 | 1 | |
| 7 | 3 | |
| 8 | 36 | |
| 9 | 35 | |
| 10 | A Survey on Multiview Clusteringbreakdown → | 272 |
| 11 | 17 | |
| 12 | 36 | |
| 13 | 26 | |
| 14 | PAC-Bayes bounds for stable algorithms with instance-dependent priors | 2 |
| 15 | 99 | |
| 16 | Revisiting Gaussian process dynamical models | 4 |
| 17 | 60 | |
| 18 | PAC-bayes bounds with data dependent priors | 33 |
| 19 | 23 | |
| 20 | Sparse Semi-supervised Learning Using Conjugate Functions | 76 |
About Shiliang Sun
Shiliang Sun is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing, having authored 197 papers that have together received 7.2k indexed citations. Recurring topics across this work include Face and Expression Recognition (47 papers), Domain Adaptation and Few-Shot Learning (37 papers) and Text and Document Classification Technologies (23 papers). The work is most often cited by research in Computational Mathematics (98 citations), Computer Vision and Pattern Recognition (2.7k citations) and Artificial Intelligence (3.7k citations). Shiliang Sun has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Jing Zhao, Xijiong Xie, Xin Xu, Guoqing Chao, John Shawe‐Taylor, Changshui Zhang, Zhu Han, Chen Luo, Junyu Chen and Rongqing Huang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Journal of The Electrochemical Society and IEEE Transactions on Image Processing.
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.