Guangxing Han
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 5%
- Media Technology top 10%
- Aerospace Engineering
- Industrial and Manufacturing Engineering top 10%
- Co-authors
- Jiawei MaShih-Fu ChangShiyuan HuangYicheng HeLong ChenXuan ZhangWael AbdAlmageedAram Galstyan
- Topics
- Domain Adaptation and Few-Shot Learning (7 papers)Advanced Neural Network Applications (5 papers)Multimodal Machine Learning Applications (4 papers)
- Journals
- IEEE Transactions on Circuits and Systems for Video Technology2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)2021 IEEE/CVF International Conference on Computer Vision (ICCV)
- Partner nations
- ChinaUnited StatesIndia
In The Last Decade
Guangxing Han
11 papers receiving 412 citations
Peers
Comparison fields: 5 of 54
- Computer Vision and Pattern Recognition 303
- Artificial Intelligence 237
- Media Technology 49
- Aerospace Engineering 49
- Industrial and Manufacturing Engineering 47
Countries citing papers authored by Guangxing Han
This map shows the geographic impact of Guangxing Han'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 Guangxing Han with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guangxing Han more than expected).
Fields of papers citing papers by Guangxing Han
This network shows the impact of papers produced by Guangxing Han. 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 Guangxing Han. The network helps show where Guangxing Han may publish in the future.
Co-authorship network of co-authors of Guangxing Han
This figure shows the co-authorship network connecting the top 25 collaborators of Guangxing Han. A scholar is included among the top collaborators of Guangxing Han 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 Guangxing Han. Guangxing Han is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | 113 | |
| 3 | 121 | |
| 4 | 26 | |
| 5 | 50 | |
| 6 | 78 | |
| 7 | 2 | |
| 8 | 11 | |
| 9 | 10 | |
| 10 | 5 | |
| 11 | 2 |
About Guangxing Han
Guangxing Han is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing, having authored 11 papers that have together received 427 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (7 papers), Advanced Neural Network Applications (5 papers) and Multimodal Machine Learning Applications (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (303 citations), Artificial Intelligence (237 citations) and Media Technology (49 citations). Guangxing Han has collaborated with scholars based in China, United States and India. Frequent co-authors include Jiawei Ma, Shih-Fu Chang, Shiyuan Huang, Yicheng He, Long Chen, Xuan Zhang, Wael AbdAlmageed, Aram Galstyan, Guo-Bo Zhang and Xuan Zhang. Their work appears in journals such as IEEE Transactions on Circuits and Systems for Video Technology, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
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.