Lipeng Ke
Impact in
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- Human Pose and Action Recognition
- Generative Adversarial Networks and Image Synthesis
- Digital Media Forensic Detection
- Face recognition and analysis
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- Hand Gesture Recognition Systems
Papers in
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- Digital Media Forensic Detection 3
- Human Pose and Action Recognition 3
- Video Surveillance and Tracking Methods 2
- Generative Adversarial Networks and Image Synthesis 2
- Face recognition and analysis 1
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- Anomaly Detection Techniques and Applications 4
- Adversarial Robustness in Machine Learning 2
- Domain Adaptation and Few-Shot Learning 1
- Co-authors
- Siwei Lyu (8 shared papers)Kuan–Chuan Peng (1 shared paper)Yan Ju (2 shared papers)Koki Nagano (1 shared paper)Hongfei Xue (1 shared paper)Shu Hu (1 shared paper)Xin Wang (1 shared paper)Honggang Qi (3 shared papers)
- Journals
- IEEE Transactions on Cybernetics (1 paper)IET conference proceedings. (1 paper)2022 IEEE International Conference on Image Processing (ICIP) (1 paper)2021 IEEE/CVF International Conference on Computer Vision (ICCV) (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)
- Partner nations
- United StatesChinaTaiwan
In The Last Decade
Lipeng Ke
8 papers receiving 140 citations
Peers
Comparison fields: 5 of 40
- Computer Vision and Pattern Recognition 102
- Human-Computer Interaction 14
- Artificial Intelligence 55
- Biomedical Engineering 35
- Signal Processing 8
Countries citing papers authored by Lipeng Ke
This map shows the geographic impact of Lipeng Ke'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 Lipeng Ke with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lipeng Ke more than expected).
Fields of papers citing papers by Lipeng Ke
This network shows the impact of papers produced by Lipeng Ke. 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 Lipeng Ke. The network helps show where Lipeng Ke may publish in the future.
Co-authors
The 15 scholars most cited alongside Lipeng Ke, 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 | 2022 | 45 | |
| 2 | 2022 | 41 | |
| 3 | 2021 | 22 | |
| 4 | 2017 | 12 | |
| 5 | 2021 | 12 | |
| 6 | 2018 | 6 | |
| 7 | 2019 | 3 | |
| 8 | 2024 | 1 | |
| 9 | 2024 | 0 |
About Lipeng Ke
Lipeng Ke is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Rehabilitation, Control and Systems Engineering and Building and Construction, having authored 9 papers that have together received 142 indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (4 papers), Digital Media Forensic Detection (3 papers), Human Pose and Action Recognition (3 papers), Video Surveillance and Tracking Methods (2 papers), Adversarial Robustness in Machine Learning (2 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Domain Adaptation and Few-Shot Learning (1 paper) and Face recognition and analysis (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (102 citations), Human-Computer Interaction (14 citations), Artificial Intelligence (55 citations), Biomedical Engineering (35 citations) and Signal Processing (8 citations). Lipeng Ke has collaborated with scholars based in United States, China and Taiwan. Frequent co-authors include Siwei Lyu, Kuan–Chuan Peng, Yan Ju, Koki Nagano, Hongfei Xue, Shu Hu, Xin Wang, Honggang Qi, Ming‐Ching Chang and Pu Sun. Their work appears in journals such as IEEE Transactions on Cybernetics, IET conference proceedings., 2022 IEEE International Conference on Image Processing (ICIP), 2021 IEEE/CVF International Conference on Computer Vision (ICCV) and Proceedings of the AAAI Conference on Artificial Intelligence.
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.