Cheng-Chun Hsu
- Computer Vision and Pattern Recognition top 10%
- Computational Mechanics
- Control and Systems Engineering
- Artificial Intelligence
- Industrial and Manufacturing Engineering
- Co-authors
- Yuke ZhuZhenyu JiangWen-Huang ChengShintami Chusnul HidayatiKai‐Lung HuaJianlong FuYu-Ting ChangLai-Kuan Wong
- Topics
- Robot Manipulation and Learning (2 papers)Generative Adversarial Networks and Image Synthesis (2 papers)Face recognition and analysis (2 papers)
- Journals
- IEEE Transactions on MultimediaFrontiers in Public Health2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
- Partner nations
- TaiwanUnited StatesMalaysia
In The Last Decade
Cheng-Chun Hsu
6 papers receiving 188 citations
Peers
Comparison fields: 5 of 51
- Computer Vision and Pattern Recognition 121
- Computational Mechanics 50
- Control and Systems Engineering 27
- Artificial Intelligence 23
- Industrial and Manufacturing Engineering 18
Countries citing papers authored by Cheng-Chun Hsu
This map shows the geographic impact of Cheng-Chun Hsu'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 Cheng-Chun Hsu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cheng-Chun Hsu more than expected).
Fields of papers citing papers by Cheng-Chun Hsu
This network shows the impact of papers produced by Cheng-Chun Hsu. 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 Cheng-Chun Hsu. The network helps show where Cheng-Chun Hsu may publish in the future.
Co-authorship network of co-authors of Cheng-Chun Hsu
This figure shows the co-authorship network connecting the top 25 collaborators of Cheng-Chun Hsu. A scholar is included among the top collaborators of Cheng-Chun Hsu 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 Cheng-Chun Hsu. Cheng-Chun Hsu 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 | 14 | |
| 3 | 4 | |
| 4 | 54 | |
| 5 | 41 | |
| 6 | 65 | |
| 7 | 13 |
About Cheng-Chun Hsu
Cheng-Chun Hsu is a scholar working on Computer Vision and Pattern Recognition, Complementary and alternative medicine and Computational Mechanics, having authored 7 papers that have together received 191 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (2 papers), Generative Adversarial Networks and Image Synthesis (2 papers) and Face recognition and analysis (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (121 citations), Museology (15 citations) and Computational Mechanics (50 citations). Cheng-Chun Hsu has collaborated with scholars based in Taiwan, United States and Malaysia. Frequent co-authors include Yuke Zhu, Zhenyu Jiang, Wen-Huang Cheng, Shintami Chusnul Hidayati, Kai‐Lung Hua, Jianlong Fu, Yu-Ting Chang, Zhenyu Jiang, Lai-Kuan Wong and John See. Their work appears in journals such as IEEE Transactions on Multimedia, Frontiers in Public Health and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
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.