Dan Song

2.1k citations
95 papers · 1.2k indexed · 1 hit paper · h-index 19
Topics
3D Shape Modeling and Analysis (29 papers)Advanced Image and Video Retrieval Techniques (22 papers)Human Pose and Action Recognition (20 papers)
Partner nations
ChinaSwedenAustralia

In The Last Decade

Dan Song

85 papers receiving 1.2k citations

Hit Papers

Illumination-aware faster R-CNN for robust multispectral ...20182026202020232018100200300

Peers

Dan Song
Comparison fields: 5 of 106
  • Computer Vision and Pattern Recognition 721
  • Artificial Intelligence 267
  • Control and Systems Engineering 249
  • Computational Mechanics 210
  • Aerospace Engineering 189
Replace Jianhui Zhao with:
Jianhui Zhao China
Xinyu Zhang China
Sehoon Ha United States
Zhaoqi Wang China
Nick Pears United Kingdom
Xinyu Huang United States
Shohei Nobuhara Japan
Ran Song China
Jiang Yu Zheng United States
Ran Xu China
Dan Song relative to Jianhui Zhao China Jianhui Zhao's profile →
Citations per field
00.5×3.1×
Jianhui Zhao · 1×
Citations per year

Countries citing papers authored by Dan Song

Since Specialization
Citations

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

Fields of papers citing papers by Dan Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dan Song

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 0
3 1
4 0
5 2
6 11
7 3
8 1
9 2
10 5
11 7
12 5
13 5
14 1
15 44
16 14
17 4
18 10
19
Topological Synergies for Grasp Transfer
1
20
Object Motion Analysis and Interpretation in Video
0

About Dan Song

Dan Song is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Computational Mechanics, having authored 95 papers that have together received 1.2k indexed citations. Recurring topics across this work include 3D Shape Modeling and Analysis (29 papers), Advanced Image and Video Retrieval Techniques (22 papers) and Human Pose and Action Recognition (20 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (721 citations), Media Technology (136 citations) and Computer Graphics and Computer-Aided Design (42 citations). Dan Song has collaborated with scholars based in China, Sweden and Australia. Frequent co-authors include Ruofeng Tong, Min Tang, Chengyang Li, Danica Kragić, An-An Liu, Weizhi Nie, Wenhui Li, Kai Huebner, Carl Henrik Ek and Ville Kyrki. Their work appears in journals such as Scientific Reports, Applied Energy and IEEE Transactions on Geoscience and Remote Sensing.

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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