Hong Wu
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 5%
- Radiology, Nuclear Medicine and Imaging
- Cognitive Neuroscience
- Electrical and Electronic Engineering
- Co-authors
- Bodi YuanZhiqiang YuanJian PengYu-Xiong WangYuanyi ZhongYong FanHanqing LuHai Wang
- Topics
- Advanced Image and Video Retrieval Techniques (12 papers)Image Retrieval and Classification Techniques (11 papers)Face and Expression Recognition (8 papers)
- Partner nations
- ChinaUnited StatesJapan
In The Last Decade
Hong Wu
57 papers receiving 648 citations
Peers
Comparison fields: 5 of 115
- Computer Vision and Pattern Recognition 298
- Artificial Intelligence 233
- Radiology, Nuclear Medicine and Imaging 107
- Cognitive Neuroscience 91
- Electrical and Electronic Engineering 50
Countries citing papers authored by Hong Wu
This map shows the geographic impact of Hong 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 Hong Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hong Wu more than expected).
Fields of papers citing papers by Hong Wu
This network shows the impact of papers produced by Hong 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 Hong Wu. The network helps show where Hong Wu may publish in the future.
Co-authorship network of co-authors of Hong Wu
This figure shows the co-authorship network connecting the top 25 collaborators of Hong Wu. A scholar is included among the top collaborators of Hong 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 Hong Wu. Hong 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 | 3 | |
| 2 | 9 | |
| 3 | 13 | |
| 4 | 9 | |
| 5 | 2 | |
| 6 | 6 | |
| 7 | 5 | |
| 8 | 1 | |
| 9 | 11 | |
| 10 | UESTC at ImageCLEF 2012 Medical Tasks | 1 |
| 11 | 4 | |
| 12 | 6 | |
| 13 | Synchronization and channel estimation for MB-OFDM based UWB systems | 0 |
| 14 | Joint PAPR Reduction and Residual CFO Synchronization for MQAM-OFDM Systems | 1 |
| 15 | 65 | |
| 16 | Research on cooperative optimization of improved estimation of distribution algorithm | 2 |
| 17 | CLASSIFYING THE SPECIES OF EXOPALAEMON BY USING VISIBLE AND NEAR INFRARED SPECTRA WITH UNINFORMATIVE VARIABLE ELIMINATION AND SUCCESSIVE PROJECTIONS ALGORITHM | 4 |
| 18 | 1 | |
| 19 | Ordinal Regression in Content-Based Image Retrieval | 1 |
| 20 | THE APPLICATION OF ARTIFICIAL NEURAL NETWORKS IN THE RESOURCES AND ENVIRONMENT | 11 |
About Hong Wu
Hong Wu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing, having authored 60 papers that have together received 682 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (12 papers), Image Retrieval and Classification Techniques (11 papers) and Face and Expression Recognition (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (298 citations), Artificial Intelligence (233 citations) and Media Technology (41 citations). Hong Wu has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Bodi Yuan, Zhiqiang Yuan, Jian Peng, Yu-Xiong Wang, Yuanyi Zhong, Yong Fan, Hanqing Lu, Hai Wang, Mao Ye and Lei Wang. Their work appears in journals such as NeuroImage, Optics Letters and Pattern Recognition.
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.