Qidong Huang
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Signal Processing
- Computational Mechanics
- Media Technology
- Co-authors
- Nenghai YuWeiming ZhangDongdong ChenJie ZhangGang HuaHan FangZehua MaXiaoyi Dong
- Topics
- Adversarial Robustness in Machine Learning (4 papers)Digital Media Forensic Detection (3 papers)3D Shape Modeling and Analysis (3 papers)
- Cited by
- Computer Vision and Pattern RecognitionArtificial IntelligenceComputer Graphics and Computer-Aided Design
- Journals
- IEEE Transactions on Image ProcessingIEEE Transactions on Circuits and Systems for Video TechnologyInternational Journal of Modern Physics C
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Qidong Huang
14 papers receiving 287 citations
Peers
Comparison fields: 5 of 49
- Computer Vision and Pattern Recognition 171
- Artificial Intelligence 141
- Signal Processing 36
- Computational Mechanics 35
- Media Technology 19
Countries citing papers authored by Qidong Huang
This map shows the geographic impact of Qidong Huang'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 Qidong Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qidong Huang more than expected).
Fields of papers citing papers by Qidong Huang
This network shows the impact of papers produced by Qidong Huang. 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 Qidong Huang. The network helps show where Qidong Huang may publish in the future.
Co-authorship network of co-authors of Qidong Huang
This figure shows the co-authorship network connecting the top 25 collaborators of Qidong Huang. A scholar is included among the top collaborators of Qidong Huang 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 Qidong Huang. Qidong Huang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 9 | |
| 6 | 23 | |
| 7 | 6 | |
| 8 | 4 | |
| 9 | 4 | |
| 10 | 30 | |
| 11 | 51 | |
| 12 | 51 | |
| 13 | 34 | |
| 14 | 78 | |
| 15 | 1 | |
| 16 | 1 |
About Qidong Huang
Qidong Huang is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Artificial Intelligence, having authored 16 papers that have together received 294 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (4 papers), Digital Media Forensic Detection (3 papers) and 3D Shape Modeling and Analysis (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (171 citations), Artificial Intelligence (141 citations) and Computer Graphics and Computer-Aided Design (12 citations). Qidong Huang has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Nenghai Yu, Weiming Zhang, Dongdong Chen, Jie Zhang, Gang Hua, Han Fang, Zehua Ma, Xiaoyi Dong, Hang Zhou and Xiaoyi Dong. Their work appears in journals such as IEEE Transactions on Image Processing, IEEE Transactions on Circuits and Systems for Video Technology and International Journal of Modern Physics C.
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.