Zeyi Huang
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 5%
- Control and Systems Engineering top 5%
- Safety, Risk, Reliability and Quality top 2%
- Organic Chemistry
- Topics
- Domain Adaptation and Few-Shot Learning (7 papers)Advanced Neural Network Applications (6 papers)RNA and protein synthesis mechanisms (5 papers)
- Cited by
- Computer Vision and Pattern RecognitionSafety, Risk, Reliability and QualityMedia Technology
- Partner nations
- United StatesChinaPoland
In The Last Decade
Zeyi Huang
22 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 114
- Computer Vision and Pattern Recognition 522
- Artificial Intelligence 290
- Control and Systems Engineering 201
- Safety, Risk, Reliability and Quality 175
- Organic Chemistry 145
Countries citing papers authored by Zeyi Huang
This map shows the geographic impact of Zeyi Huang'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 Zeyi Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zeyi Huang more than expected).
Fields of papers citing papers by Zeyi Huang
This network shows the impact of papers produced by Zeyi Huang. 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 Zeyi Huang. The network helps show where Zeyi Huang may publish in the future.
Co-authorship network of co-authors of Zeyi Huang
This figure shows the co-authorship network connecting the top 25 collaborators of Zeyi Huang. A scholar is included among the top collaborators of Zeyi Huang 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 Zeyi Huang. Zeyi Huang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 5 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 12 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 0 | |
| 10 | 8 | |
| 11 | 42 | |
| 12 | 2 | |
| 13 | On the Integration of Self-Attention and Convolutionbreakdown → | 329 |
| 14 | 11 | |
| 15 | Comprehensive Attention Self-Distillation for Weakly-Supervised Object Detection | 5 |
| 16 | 19 | |
| 17 | 142 | |
| 18 | 91 | |
| 19 | 109 | |
| 20 | 6 |
About Zeyi Huang
Zeyi Huang is a scholar working on Computer Vision and Pattern Recognition, Safety, Risk, Reliability and Quality and Artificial Intelligence, having authored 27 papers that have together received 1.3k indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (7 papers), Advanced Neural Network Applications (6 papers) and RNA and protein synthesis mechanisms (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (522 citations), Safety, Risk, Reliability and Quality (175 citations) and Media Technology (114 citations). Zeyi Huang has collaborated with scholars based in United States, China and Poland. Frequent co-authors include Eric P. Xing, Haohan Wang, Xindi Wu, Zhengguo Xu, Wenhai Wang, Youxian Sun, Rui Lü, Xuran Pan, Shiji Song and Guan-Fu Chen. Their work appears in journals such as Chemical Reviews, Angewandte Chemie International Edition and Nature Methods.
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.