Zhenyong Fu
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 2%
- Radiology, Nuclear Medicine and Imaging top 10%
- Ocean Engineering top 10%
- Cancer Research
- Topics
- Domain Adaptation and Few-Shot Learning (11 papers)Multimodal Machine Learning Applications (8 papers)Human Pose and Action Recognition (3 papers)
- Cited by
- Computer Vision and Pattern RecognitionArtificial IntelligenceRadiology, Nuclear Medicine and Imaging
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceInternational Journal of Computer VisionNeurocomputing
- Partner nations
- ChinaUnited KingdomJapan
In The Last Decade
Zhenyong Fu
13 papers receiving 793 citations
Hit Papers
Peers
Comparison fields: 5 of 61
- Artificial Intelligence 689
- Computer Vision and Pattern Recognition 518
- Radiology, Nuclear Medicine and Imaging 177
- Ocean Engineering 74
- Cancer Research 58
Countries citing papers authored by Zhenyong Fu
This map shows the geographic impact of Zhenyong 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 Zhenyong Fu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zhenyong Fu more than expected).
Fields of papers citing papers by Zhenyong Fu
This network shows the impact of papers produced by Zhenyong 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 Zhenyong Fu. The network helps show where Zhenyong Fu may publish in the future.
Co-authorship network of co-authors of Zhenyong Fu
This figure shows the co-authorship network connecting the top 25 collaborators of Zhenyong Fu. A scholar is included among the top collaborators of Zhenyong 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 Zhenyong Fu. Zhenyong 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 | 3 | |
| 2 | 2 | |
| 3 | 19 | |
| 4 | 4 | |
| 5 | Contrastive Embedding for Generalized Zero-Shot Learningbreakdown → | 175 |
| 6 | 77 | |
| 7 | 12 | |
| 8 | 72 | |
| 9 | 9 | |
| 10 | 243 | |
| 11 | 147 | |
| 12 | 23 | |
| 13 | 16 |
About Zhenyong Fu
Zhenyong Fu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing, having authored 13 papers that have together received 802 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (11 papers), Multimodal Machine Learning Applications (8 papers) and Human Pose and Action Recognition (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (518 citations), Artificial Intelligence (689 citations) and Radiology, Nuclear Medicine and Imaging (177 citations). Zhenyong Fu has collaborated with scholars based in China, United Kingdom and Japan. Frequent co-authors include Elyor Kodirov, Tao Xiang, Shaogang Gong, Zongyan Han, Jian Yang, Shuo Chen, Yunyun Wang, Jian Yang, Songcan Chen and Zhiwu Lu. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision and Neurocomputing.
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.