Qinghua Hu
- Computer Vision and Pattern Recognition top 0.05%
- Artificial Intelligence top 0.05%
- Computational Theory and Mathematics top 0.01%
- Information Systems top 0.05%
- Media Technology top 0.1%
- Topics
- Rough Sets and Fuzzy Logic (99 papers)Domain Adaptation and Few-Shot Learning (58 papers)Face and Expression Recognition (57 papers)
- Cited by
- Computer Vision and Pattern RecognitionComputational Theory and MathematicsArtificial Intelligence
- Journals
- SHILAP Revista de lepidopterologíaBioinformaticsThe Astrophysical Journal
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Qinghua Hu
406 papers receiving 22.5k citations
Hit Papers
Peers
Comparison fields: 5 of 209
- Computer Vision and Pattern Recognition 9.3k
- Artificial Intelligence 8.7k
- Computational Theory and Mathematics 6.2k
- Information Systems 4.0k
- Media Technology 2.1k
Countries citing papers authored by Qinghua Hu
This map shows the geographic impact of Qinghua 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 Qinghua Hu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qinghua Hu more than expected).
Fields of papers citing papers by Qinghua Hu
This network shows the impact of papers produced by Qinghua 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 Qinghua Hu. The network helps show where Qinghua Hu may publish in the future.
Co-authorship network of co-authors of Qinghua Hu
This figure shows the co-authorship network connecting the top 25 collaborators of Qinghua Hu. A scholar is included among the top collaborators of Qinghua 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 Qinghua Hu. Qinghua 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 | 1 | |
| 3 | 0 | |
| 4 | 3 | |
| 5 | 3 | |
| 6 | 2 | |
| 7 | 3 | |
| 8 | 8 | |
| 9 | 5 | |
| 10 | 11 | |
| 11 | 9 | |
| 12 | 2 | |
| 13 | 8 | |
| 14 | 37 | |
| 15 | 2 | |
| 16 | 8 | |
| 17 | Enhancing Geometric Factors in Model Learning and Inference for Object Detection and Instance Segmentationbreakdown → | 891 |
| 18 | 20 | |
| 19 | 6 | |
| 20 | 213 |
About Qinghua Hu
Qinghua Hu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Theory and Mathematics, having authored 431 papers that have together received 23.1k indexed citations. Recurring topics across this work include Rough Sets and Fuzzy Logic (99 papers), Domain Adaptation and Few-Shot Learning (58 papers) and Face and Expression Recognition (57 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (9.3k citations), Computational Theory and Mathematics (6.2k citations) and Artificial Intelligence (8.7k citations). Qinghua Hu has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Pengfei Zhu, Wangmeng Zuo, Daren Yu, Qilong Wang, Peihua Li, Degang Chen, Zongxia Xie, Jinfu Liu, Changzhong Wang and Dongwei Ren. Their work appears in journals such as SHILAP Revista de lepidopterología, Bioinformatics and The Astrophysical Journal.
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.