Pengguang Chen
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- Advanced Image and Video Retrieval Techniques 5
- Advanced Neural Network Applications 4
- Multimodal Machine Learning Applications 1
- Artificial Intelligence top 5%
- Domain Adaptation and Few-Shot Learning 6
- Machine Learning and Algorithms 1
- Media Technology top 10%
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- Smart Materials for Construction 1
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- Surface Modification and Superhydrophobicity 1
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- Mineral Processing and Grinding 1
- Co-authors
- Jiaya JiaShu LiuHengshuang ZhaoXing Quan WangCheuk Lun ChowDenvid LauXiaoyong ShenJiequan Cui
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence (3 papers)Matter (1 paper)Chemical Engineering Science (1 paper)
- Partner nations
- Hong KongUnited StatesChina
In The Last Decade
Pengguang Chen
9 papers receiving 480 citations
Hit Papers
Peers
Comparison fields: 5 of 85
- Computer Vision and Pattern Recognition 250
- Artificial Intelligence 244
- Media Technology 33
- Computational Mathematics 2
- Industrial and Manufacturing Engineering 26
Countries citing papers authored by Pengguang Chen
This map shows the geographic impact of Pengguang Chen'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 Pengguang Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pengguang Chen more than expected).
Fields of papers citing papers by Pengguang Chen
This network shows the impact of papers produced by Pengguang Chen. 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 Pengguang Chen. The network helps show where Pengguang Chen may publish in the future.
Co-authorship network
The 24 scholars most cited alongside Pengguang Chen, 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 | 2025 | 0 | |
| 2 | 2024 | 2 | |
| 3 | 2023 | 5 | |
| 4 | 2023 | 59 | |
| 5 | 2023 | 28 | |
| 6 | 2022 | 17 | |
| 7 | Distilling Knowledge via Knowledge Reviewbreakdown → | 2021 | 285 |
| 8 | 2021 | 49 | |
| 9 | 2021 | 8 | |
| 10 | 2019 | 43 |
About Pengguang Chen
Pengguang Chen is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Surfaces, Coatings and Films, having authored 10 papers that have together received 496 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (6 papers), Advanced Image and Video Retrieval Techniques (5 papers), Advanced Neural Network Applications (4 papers), Smart Materials for Construction (1 paper), Surface Modification and Superhydrophobicity (1 paper), Mineral Processing and Grinding (1 paper), Multimodal Machine Learning Applications (1 paper) and Machine Learning and Algorithms (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (250 citations), Artificial Intelligence (244 citations) and Media Technology (33 citations). Pengguang Chen has collaborated with scholars based in Hong Kong, United States and China. Frequent co-authors include Jiaya Jia, Shu Liu, Hengshuang Zhao, Xing Quan Wang, Cheuk Lun Chow, Shu Liu, Denvid Lau, Xiaoyong Shen, Jiequan Cui and Ruiyu Li. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Matter, Chemical Engineering Science, Rare & Special e-Zone (The Hong Kong University of Science and Technology) and 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
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.