Shu Hu
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- General Health Professions
- Sociology and Political Science
- Clinical Psychology
- Co-authors
- Siwei LyuLie WangMing‐Ching ChangGuoyuan SuiXin WangGuo HuiLi LiuLei Ma
- Topics
- Generative Adversarial Networks and Image Synthesis (15 papers)Digital Media Forensic Detection (10 papers)Advanced Neural Network Applications (7 papers)
- Cited by
- Computer Vision and Pattern RecognitionArtificial IntelligenceOrganizational Behavior and Human Resource Management
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE AccessPattern Recognition
- Partner nations
- United StatesChinaTaiwan
In The Last Decade
Shu Hu
51 papers receiving 570 citations
Peers
Comparison fields: 5 of 88
- Computer Vision and Pattern Recognition 252
- Artificial Intelligence 167
- General Health Professions 61
- Sociology and Political Science 47
- Clinical Psychology 46
Countries citing papers authored by Shu Hu
This map shows the geographic impact of Shu Hu'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 Shu Hu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shu Hu more than expected).
Fields of papers citing papers by Shu Hu
This network shows the impact of papers produced by Shu Hu. 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 Shu Hu. The network helps show where Shu Hu may publish in the future.
Co-authorship network of co-authors of Shu Hu
This figure shows the co-authorship network connecting the top 25 collaborators of Shu Hu. A scholar is included among the top collaborators of Shu Hu 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 Shu Hu. Shu Hu 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 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 4 | |
| 7 | 3 | |
| 8 | 3 | |
| 9 | 7 | |
| 10 | 7 | |
| 11 | 3 | |
| 12 | 1 | |
| 13 | 6 | |
| 14 | 18 | |
| 15 | 4 | |
| 16 | 2 | |
| 17 | 34 | |
| 18 | Uncertainty Aware Semi-Supervised Learning on Graph Data | 1 |
| 19 | Design and implementation of mobile widget composition framework and tool for end-user | 3 |
| 20 | Approximate K-Median of Location Streams with Redundancy and Inconsistency. | 1 |
About Shu Hu
Shu Hu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing, having authored 58 papers that have together received 588 indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (15 papers), Digital Media Forensic Detection (10 papers) and Advanced Neural Network Applications (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (252 citations), Artificial Intelligence (167 citations) and Organizational Behavior and Human Resource Management (37 citations). Shu Hu has collaborated with scholars based in United States, China and Taiwan. Frequent co-authors include Siwei Lyu, Lie Wang, Ming‐Ching Chang, Guoyuan Sui, Xin Wang, Guo Hui, Li Liu, Lei Ma, Huawen Liu and Thuc Duy Le. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Access 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.