Chi Li
Impact in
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- Advanced Neural Network Applications
- Advanced Vision and Imaging
- Advanced Image and Video Retrieval Techniques
- Human Pose and Action Recognition
- Video Surveillance and Tracking Methods
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- Remote-Sensing Image Classification
Papers in
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- Advanced Vision and Imaging 4
- Advanced Neural Network Applications 3
- Advanced Image Processing Techniques 2
- Advanced Image and Video Retrieval Techniques 2
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- Robotics and Sensor-Based Localization 4
- Co-authors
- Gregory D. Hager (4 shared papers)Quoc-Huy Tran (2 shared papers)M. Zeeshan Zia (2 shared papers)Manmohan Chandraker (2 shared papers)Xiang Yu (1 shared paper)Yu Xiang (1 shared paper)Weiwei Kong (2 shared papers)Chong You (1 shared paper)
- Journals
- Frontiers in Neurorobotics (1 paper)IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)Signal Image and Video Processing (1 paper)Advanced materials research (1 paper)
- Partner nations
- ChinaUnited StatesItaly
In The Last Decade
Chi Li
10 papers receiving 168 citations
Peers
Comparison fields: 5 of 50
- Computer Vision and Pattern Recognition 129
- Media Technology 24
- Aerospace Engineering 58
- Computer Graphics and Computer-Aided Design 5
- Artificial Intelligence 46
Countries citing papers authored by Chi Li
This map shows the geographic impact of Chi Li'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 Chi Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chi Li more than expected).
Fields of papers citing papers by Chi Li
This network shows the impact of papers produced by Chi Li. 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 Chi Li. The network helps show where Chi Li may publish in the future.
Co-authors
The 22 scholars most cited alongside Chi Li, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 58 | |
| 2 | 2017 | 56 | |
| 3 | 2016 | 17 | |
| 4 | 2016 | 17 | |
| 5 | Scalable Exemplar-based Subspace Clustering on Class-Imbalanced Data | 2018 | 15 |
| 6 | 2022 | 11 | |
| 7 | 2012 | 5 | |
| 8 | 2023 | 1 | |
| 9 | 2018 | 1 | |
| 10 | 2023 | 1 |
About Chi Li
Chi Li is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Information Systems, Artificial Intelligence and Media Technology, having authored 10 papers that have together received 182 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (4 papers), Advanced Vision and Imaging (4 papers), Advanced Neural Network Applications (3 papers), Advanced Image Processing Techniques (2 papers), Advanced Image and Video Retrieval Techniques (2 papers), Remote-Sensing Image Classification (1 paper), Caching and Content Delivery (1 paper) and Image Processing Techniques and Applications (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (129 citations), Media Technology (24 citations), Aerospace Engineering (58 citations), Computer Graphics and Computer-Aided Design (5 citations) and Artificial Intelligence (46 citations). Chi Li has collaborated with scholars based in China, United States and Italy. Frequent co-authors include Gregory D. Hager, Quoc-Huy Tran, M. Zeeshan Zia, Manmohan Chandraker, Xiang Yu, Yu Xiang, Weiwei Kong, Chong You, Daniel P. Robinson and Lei Yang. Their work appears in journals such as Frontiers in Neurorobotics, IEEE Transactions on Pattern Analysis and Machine Intelligence, Signal Image and Video Processing and Advanced materials research.
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.