Dian Gong

426 citations
10 papers · 187 indexed · h-index 5
Topics
Face and Expression Recognition (3 papers)Medical Image Segmentation Techniques (3 papers)Image and Signal Denoising Methods (2 papers)
Journals
IEEE Transactions on Pattern Analysis and Machine IntelligenceEurope PMC (PubMed Central)PubMed

In The Last Decade

Dian Gong

10 papers receiving 177 citations

Peers

Dian Gong
Comparison fields: 5 of 48
  • Computer Vision and Pattern Recognition 139
  • Artificial Intelligence 70
  • Signal Processing 42
  • Biomedical Engineering 39
  • Control and Systems Engineering 29
Replace Tai-Peng Tian with:
Tai-Peng Tian United States
Hanno Wirtz Germany
Leonid Taycher United States
Tobias Kirschstein Germany
Zhanning Gao China
Ming-Yu Liu United States
Xinyue Liu China
Anchit Gupta India
André Schulz Germany
Noreen Kausar Malaysia
Dian Gong relative to Tai-Peng Tian United States Tai-Peng Tian's profile →
Citations per field
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Tai-Peng Tian · 1×
Citations per year

Countries citing papers authored by Dian Gong

Since Specialization
Citations

This map shows the geographic impact of Dian Gong'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 Dian Gong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dian Gong more than expected).

Fields of papers citing papers by Dian Gong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dian Gong. 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 Dian Gong. The network helps show where Dian Gong may publish in the future.

Co-authorship network of co-authors of Dian Gong

This figure shows the co-authorship network connecting the top 25 collaborators of Dian Gong. A scholar is included among the top collaborators of Dian Gong 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 Dian Gong. Dian Gong 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 22
2 77
3
Robust Multiple Manifold Structure Learning.
6
4 4
5 56
6
Locally Linear Denoising on Image Manifolds.
1
7
Locally linear denoising on image manifolds.
15
8 1
9 1
10 4

About Dian Gong

Dian Gong is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Biophysics, having authored 10 papers that have together received 187 indexed citations. Recurring topics across this work include Face and Expression Recognition (3 papers), Medical Image Segmentation Techniques (3 papers) and Image and Signal Denoising Methods (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (139 citations), Human-Computer Interaction (27 citations) and Signal Processing (42 citations). Dian Gong has collaborated with scholars based in United States, China and Belgium. Frequent co-authors include Gérard Medioni, Xuemei Zhao, Fei Sha, Patrick Ross, Randall C. Wetzel, David C. Kale, Zhengping Che, Yan Liu, Qiong Yang and Jianhua Lü. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Europe PMC (PubMed Central) and PubMed.

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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