Jun Huan
Impact in
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- Graph Theory and Algorithms
- Signal Processing top 2%
- Data Management and Algorithms
Papers in
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- Domain Adaptation and Few-Shot Learning 19
- Machine Learning and ELM 8
- Machine Learning and Algorithms 6
- Machine Learning and Data Classification 6
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- Graph Theory and Algorithms 7
- Advanced Neural Network Applications 6
- Multimodal Machine Learning Applications 5
- Co-authors
- Jan F. Prins (5 shared papers)Wei Wang (7 shared papers)Brian Quanz (3 shared papers)Jiong Yang (1 shared paper)Jintao Zhang (1 shared paper)Haoyi Xiong (16 shared papers)Jack Snoeyink (7 shared papers)Tianyang Wang (4 shared papers)
- Journals
- ACM Transactions on Knowledge Discovery from Data (5 papers)IEEE Transactions on Knowledge and Data Engineering (2 papers)ACM Transactions on Intelligent Systems and Technology (2 papers)IEEE/ACM Transactions on Computational Biology and Bioinformatics (1 paper)Neurocomputing (1 paper)
- Partner nations
- United StatesChinaSingapore
In The Last Decade
Jun Huan
53 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 103
- Computer Vision and Pattern Recognition 556
- Signal Processing 271
- Information Systems 429
- Artificial Intelligence 603
- Computational Mathematics 7
Countries citing papers authored by Jun Huan
This map shows the geographic impact of Jun Huan'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 Jun Huan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Huan more than expected).
Fields of papers citing papers by Jun Huan
This network shows the impact of papers produced by Jun Huan. 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 Jun Huan. The network helps show where Jun Huan may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Huan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 54 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2004 | 390 | |
| 2 | 2004 | 208 | |
| 3 | 2009 | 104 | |
| 4 | 2012 | 90 | |
| 5 | 2004 | 68 | |
| 6 | 2020 | 48 | |
| 7 | 2012 | 48 | |
| 8 | 2021 | 36 | |
| 9 | 2019 | 32 | |
| 10 | 2019 | 25 | |
| 11 | 2018 | 22 | |
| 12 | 2020 | 21 | |
| 13 | 2006 | 20 | |
| 14 | 2011 | 17 | |
| 15 | 2015 | 17 | |
| 16 | 2022 | 16 | |
| 17 | 2021 | 16 | |
| 18 | 2011 | 16 | |
| 19 | 2020 | 13 | |
| 20 | 2019 | 11 |
About Jun Huan
Jun Huan is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, Computational Mechanics and Signal Processing, having authored 54 papers that have together received 1.4k indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (19 papers), Machine Learning and ELM (8 papers), Sparse and Compressive Sensing Techniques (7 papers), Graph Theory and Algorithms (7 papers), Advanced Neural Network Applications (6 papers), Machine Learning and Algorithms (6 papers), Machine Learning and Data Classification (6 papers) and Multimodal Machine Learning Applications (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (556 citations), Signal Processing (271 citations), Information Systems (429 citations), Artificial Intelligence (603 citations) and Computational Mathematics (7 citations). Jun Huan has collaborated with scholars based in United States, China and Singapore. Frequent co-authors include Jan F. Prins, Wei Wang, Brian Quanz, Jiong Yang, Jintao Zhang, Haoyi Xiong, Jack Snoeyink, Tianyang Wang, Deepak Bandyopadhyay and Alexander Tropsha. Their work appears in journals such as ACM Transactions on Knowledge Discovery from Data, IEEE Transactions on Knowledge and Data Engineering, ACM Transactions on Intelligent Systems and Technology, IEEE/ACM Transactions on Computational Biology and Bioinformatics and Neurocomputing.
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.