Zhenyu Wu
- Computer Vision and Pattern Recognition top 2%
- Signal Processing top 5%
- Computer Networks and Communications top 10%
- Artificial Intelligence top 10%
- Electrical and Electronic Engineering
- Co-authors
- Jill M. BoyceMichael W. MarcellinAli BilginSushil JajodiaXin RuanHaining WangHongyang YuChang Wen Chen
- Topics
- Advanced Data Compression Techniques (23 papers)Video Coding and Compression Technologies (15 papers)Image and Signal Denoising Methods (13 papers)
- Cited by
- Computer Vision and Pattern RecognitionSignal ProcessingComputer Networks and Communications
- Partner nations
- United StatesChinaTaiwan
In The Last Decade
Zhenyu Wu
67 papers receiving 659 citations
Peers
Comparison fields: 5 of 81
- Computer Vision and Pattern Recognition 403
- Signal Processing 202
- Computer Networks and Communications 123
- Artificial Intelligence 111
- Electrical and Electronic Engineering 81
Countries citing papers authored by Zhenyu Wu
This map shows the geographic impact of Zhenyu Wu'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 Zhenyu Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zhenyu Wu more than expected).
Fields of papers citing papers by Zhenyu Wu
This network shows the impact of papers produced by Zhenyu Wu. 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 Zhenyu Wu. The network helps show where Zhenyu Wu may publish in the future.
Co-authorship network of co-authors of Zhenyu Wu
This figure shows the co-authorship network connecting the top 25 collaborators of Zhenyu Wu. A scholar is included among the top collaborators of Zhenyu Wu 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 Zhenyu Wu. Zhenyu Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 1 | |
| 3 | 6 | |
| 4 | 5 | |
| 5 | 0 | |
| 6 | 13 | |
| 7 | 13 | |
| 8 | 2 | |
| 9 | 55 | |
| 10 | 4 | |
| 11 | 52 | |
| 12 | Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions | 6 |
| 13 | 1 | |
| 14 | 11 | |
| 15 | Video transcoding to support random access in scalable video coding | 1 |
| 16 | Issues about the nocebo phenomena in clinics. | 3 |
| 17 | 5 | |
| 18 | 1 | |
| 19 | LDPC-BASED ITERATIVE JOINT SOURCE/CHANNEL DECODING SCHEME FOR JPEG2000 | 1 |
| 20 | 1 |
About Zhenyu Wu
Zhenyu Wu is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Family Practice, having authored 74 papers that have together received 680 indexed citations. Recurring topics across this work include Advanced Data Compression Techniques (23 papers), Video Coding and Compression Technologies (15 papers) and Image and Signal Denoising Methods (13 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (403 citations), Signal Processing (202 citations) and Computer Networks and Communications (123 citations). Zhenyu Wu has collaborated with scholars based in United States, China and Taiwan. Frequent co-authors include Jill M. Boyce, Michael W. Marcellin, Ali Bilgin, Sushil Jajodia, Xin Ruan, Haining Wang, Hongyang Yu, Chang Wen Chen, Zhangyang Wang and Zhiping Ying. Their work appears in journals such as PLoS ONE, IEEE Transactions on Image Processing and Computer.
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.