Chuanming Song

541 total citations
35 papers, 399 citations indexed

About

Chuanming Song is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Signal Processing. According to data from OpenAlex, Chuanming Song has authored 35 papers receiving a total of 399 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Computer Vision and Pattern Recognition, 24 papers in Media Technology and 4 papers in Signal Processing. Recurrent topics in Chuanming Song's work include Advanced Image Fusion Techniques (15 papers), Remote-Sensing Image Classification (13 papers) and Image and Signal Denoising Methods (12 papers). Chuanming Song is often cited by papers focused on Advanced Image Fusion Techniques (15 papers), Remote-Sensing Image Classification (13 papers) and Image and Signal Denoising Methods (12 papers). Chuanming Song collaborates with scholars based in China and United States. Chuanming Song's co-authors include Xianghai Wang, Ruoxi Song, Yanwen Guo, Zhi‐Hua Zhou, Yanwei Fu, Feng Liu, Yining Feng, Xiaoyang Zhao, Bo Fu and Ximing Li and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, IEEE Access and Information Sciences.

In The Last Decade

Chuanming Song

31 papers receiving 386 citations

Peers

Chuanming Song
Comparison fields: 5 of 59
  • Computer Vision and Pattern Recognition 262
  • Media Technology 186
  • Signal Processing 82
  • Atmospheric Science 48
  • Artificial Intelligence 41
Replace Ufuk Sakarya with:
Ufuk Sakarya Türkiye
Ping-Hao Wu United States
Yufei Yang China
Ewa Kijak France
Zhixiang Chen China
Yong-Huai Huang Taiwan
Ketan Kotwal Switzerland
Longbin Yan China
Ufuk Sakarya Türkiye View profile →
Citations per field, relative to Chuanming Song
Chuanming Song · 1×
Citations per year, relative to Chuanming Song
Chuanming Song · 1×

Countries citing papers authored by Chuanming Song

Since Specialization
Citations

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

Fields of papers citing papers by Chuanming Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chuanming Song

This figure shows the co-authorship network connecting the top 25 collaborators of Chuanming Song. A scholar is included among the top collaborators of Chuanming 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 Chuanming Song. Chuanming 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
# Work Indexed citations
1 1
2 3
3 3
4 0
5 2
6 2
7 2
8 2
9 2
10 109
11 9
12 3
13 1
14 1
15 35
16 6
17 10
18 1
19 4
20 137

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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