Zhaoyu Chen
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 5%
- Molecular Biology
- Experimental and Cognitive Psychology
- Signal Processing top 10%
- Topics
- Adversarial Robustness in Machine Learning (13 papers)Anomaly Detection Techniques and Applications (11 papers)Visual Attention and Saliency Detection (5 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceWater ResearchJournal of Virology
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Zhaoyu Chen
40 papers receiving 572 citations
Hit Papers
Peers
Comparison fields: 5 of 95
- Computer Vision and Pattern Recognition 238
- Artificial Intelligence 224
- Molecular Biology 59
- Experimental and Cognitive Psychology 50
- Signal Processing 44
Countries citing papers authored by Zhaoyu Chen
This map shows the geographic impact of Zhaoyu Chen'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 Zhaoyu Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zhaoyu Chen more than expected).
Fields of papers citing papers by Zhaoyu Chen
This network shows the impact of papers produced by Zhaoyu Chen. 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 Zhaoyu Chen. The network helps show where Zhaoyu Chen may publish in the future.
Co-authorship network of co-authors of Zhaoyu Chen
This figure shows the co-authorship network connecting the top 25 collaborators of Zhaoyu Chen. A scholar is included among the top collaborators of Zhaoyu Chen 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 Zhaoyu Chen. Zhaoyu Chen 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 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 0 | |
| 7 | 0 | |
| 8 | 0 | |
| 9 | 1 | |
| 10 | 10 | |
| 11 | OneTracker: Unifying Visual Object Tracking with Foundation Models and Efficient Tuningbreakdown → | 46 |
| 12 | 3 | |
| 13 | 3 | |
| 14 | 3 | |
| 15 | 16 | |
| 16 | 5 | |
| 17 | 4 | |
| 18 | 1 | |
| 19 | 1 | |
| 20 | 32 |
About Zhaoyu Chen
Zhaoyu Chen is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Graphics and Computer-Aided Design, having authored 50 papers that have together received 579 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (13 papers), Anomaly Detection Techniques and Applications (11 papers) and Visual Attention and Saliency Detection (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (238 citations), Artificial Intelligence (224 citations) and Signal Processing (44 citations). Zhaoyu Chen has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Wenqiang Zhang, Qinghua Cui, Lijun Rong, Bo Li, Dingkang Yang, Ruikun Du, Shouhong Ding, Yuzheng Wang, Zhi Tang and Kai‐Kuang Ma. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Water Research and Journal of Virology.
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.