Pengguang Chen

844 citations
10 papers · 496 indexed · 1 hit paper · h-index 7
Topics
Domain Adaptation and Few-Shot Learning (6 papers)Advanced Image and Video Retrieval Techniques (5 papers)Advanced Neural Network Applications (4 papers)

In The Last Decade

Pengguang Chen

9 papers receiving 480 citations

Hit Papers

Distilling Knowledge via Knowledge Review2021202620222024202150100150200250

Peers

Pengguang Chen
Comparison fields: 5 of 85
  • Computer Vision and Pattern Recognition 250
  • Artificial Intelligence 244
  • Media Technology 33
  • Civil and Structural Engineering 32
  • Aerospace Engineering 30
Replace Yiru Zhao with:
Yiru Zhao China
Zhichao Song China
Haibing Wu China
Jihun Kim South Korea
Yifan Yang China
Ling Zheng China
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Pengguang Chen relative to Yiru Zhao China Yiru Zhao's profile →
Citations per field
00.5×
Yiru Zhao · 1×
Citations per year

Countries citing papers authored by Pengguang Chen

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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 of co-authors of Pengguang Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Pengguang Chen. A scholar is included among the top collaborators of Pengguang Chen 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 Pengguang Chen. Pengguang Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

10 of 10 papers shown
#WorkIndexed citations
1 0
2 2
3 5
4 59
5 28
6 17
7
Distilling Knowledge via Knowledge Reviewbreakdown →
285
8 49
9 8
10 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) and Advanced Neural Network Applications (4 papers). 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, Chemical Engineering Science and Matter.

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.

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