Chen Huang
- Computer Vision and Pattern Recognition top 1%
- Artificial Intelligence top 2%
- Electrical and Electronic Engineering
- Radiology, Nuclear Medicine and Imaging top 10%
- Aerospace Engineering top 10%
- Co-authors
- Chen Change LoyXiaoou TangYining LiSimon LuceyDeva RamananHamed Kiani GaloogahiAshton FaggYuhang Zang
- Topics
- Domain Adaptation and Few-Shot Learning (6 papers)Face recognition and analysis (5 papers)Video Surveillance and Tracking Methods (5 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceRSC AdvancesIEEE Transactions on Neural Networks and Learning Systems
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Chen Huang
20 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 145
- Computer Vision and Pattern Recognition 1.2k
- Artificial Intelligence 725
- Electrical and Electronic Engineering 133
- Radiology, Nuclear Medicine and Imaging 125
- Aerospace Engineering 116
Countries citing papers authored by Chen Huang
This map shows the geographic impact of Chen 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 Chen Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chen Huang more than expected).
Fields of papers citing papers by Chen Huang
This network shows the impact of papers produced by Chen 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 Chen Huang. The network helps show where Chen Huang may publish in the future.
Co-authorship network of co-authors of Chen Huang
This figure shows the co-authorship network connecting the top 25 collaborators of Chen Huang. A scholar is included among the top collaborators of Chen 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 Chen Huang. Chen 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 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 14 | |
| 7 | 74 | |
| 8 | 9 | |
| 9 | 220 | |
| 10 | 127 | |
| 11 | 46 | |
| 12 | 23 | |
| 13 | 27 | |
| 14 | 79 | |
| 15 | 6 | |
| 16 | Local similarity-aware deep feature embedding | 46 |
| 17 | 66 | |
| 18 | Learning Deep Representation for Imbalanced Classificationbreakdown → | 627 |
| 19 | 5 | |
| 20 | 3 |
About Chen Huang
Chen Huang is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Artificial Intelligence, having authored 25 papers that have together received 1.9k indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (6 papers), Face recognition and analysis (5 papers) and Video Surveillance and Tracking Methods (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.2k citations), Artificial Intelligence (725 citations) and Media Technology (104 citations). Chen Huang has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Chen Change Loy, Xiaoou Tang, Yining Li, Simon Lucey, Deva Ramanan, Yining Li, Hamed Kiani Galoogahi, Ashton Fagg, Yuhang Zang and Alex F. Chen. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, RSC Advances and IEEE Transactions on Neural Networks and Learning Systems.
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.