Jen-tse Huang
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition
- Signal Processing
- Electrical and Electronic Engineering
- Hardware and Architecture
- Co-authors
- Michael R. LyuWenxuan WangJianping ZhangYuxin SuYizhan HuangWeibin WuPinjia HeWenxiang Jiao
- Topics
- Topic Modeling (4 papers)Adversarial Robustness in Machine Learning (4 papers)Natural Language Processing Techniques (3 papers)
- Journals
- Neurocomputing2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)Rare & Special e-Zone (The Hong Kong University of Science and Technology)
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Jen-tse Huang
13 papers receiving 175 citations
Peers
Comparison fields: 5 of 50
- Artificial Intelligence 142
- Computer Vision and Pattern Recognition 39
- Signal Processing 34
- Electrical and Electronic Engineering 16
- Hardware and Architecture 14
Countries citing papers authored by Jen-tse Huang
This map shows the geographic impact of Jen-tse 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 Jen-tse Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jen-tse Huang more than expected).
Fields of papers citing papers by Jen-tse Huang
This network shows the impact of papers produced by Jen-tse 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 Jen-tse Huang. The network helps show where Jen-tse Huang may publish in the future.
Co-authorship network of co-authors of Jen-tse Huang
This figure shows the co-authorship network connecting the top 25 collaborators of Jen-tse Huang. A scholar is included among the top collaborators of Jen-tse 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 Jen-tse Huang. Jen-tse 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 | 1 | |
| 4 | 3 | |
| 5 | 2 | |
| 6 | 11 | |
| 7 | 6 | |
| 8 | 0 | |
| 9 | 0 | |
| 10 | 7 | |
| 11 | 1 | |
| 12 | 14 | |
| 13 | 9 | |
| 14 | 27 | |
| 15 | 3 | |
| 16 | 84 | |
| 17 | 11 |
About Jen-tse Huang
Jen-tse Huang is a scholar working on Software, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 17 papers that have together received 179 indexed citations. Recurring topics across this work include Topic Modeling (4 papers), Adversarial Robustness in Machine Learning (4 papers) and Natural Language Processing Techniques (3 papers). The work is most often cited by research in Artificial Intelligence (142 citations), Signal Processing (34 citations) and Hardware and Architecture (14 citations). Jen-tse Huang has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Michael R. Lyu, Wenxuan Wang, Jianping Zhang, Yuxin Su, Yizhan Huang, Weibin Wu, Wenxuan Wang, Pinjia He, Wenxiang Jiao and Xiaosen Wang. Their work appears in journals such as Neurocomputing, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and Rare & Special e-Zone (The Hong Kong University of Science and Technology).
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.