Wei Song

1.2k total citations
96 papers, 833 citations indexed

About

Wei Song is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, Wei Song has authored 96 papers receiving a total of 833 indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Computer Vision and Pattern Recognition, 19 papers in Artificial Intelligence and 13 papers in Media Technology. Recurrent topics in Wei Song's work include Advanced Image Processing Techniques (9 papers), Advanced Image Fusion Techniques (7 papers) and Energy Efficient Wireless Sensor Networks (6 papers). Wei Song is often cited by papers focused on Advanced Image Processing Techniques (9 papers), Advanced Image Fusion Techniques (7 papers) and Energy Efficient Wireless Sensor Networks (6 papers). Wei Song collaborates with scholars based in China, United States and South Korea. Wei Song's co-authors include Rui Zheng, Zhaojun Xue, Dong Ming, Baikun Wan, Shijiu Jin, Antai Wang, Xiaobing Zhao, Yunfeng Peng, Guanghan Peng and Jianjun Hou and has published in prestigious journals such as Blood, The Astrophysical Journal and Expert Systems with Applications.

In The Last Decade

Wei Song

81 papers receiving 791 citations

Peers

Wei Song
Comparison fields: 5 of 98
  • Computer Vision and Pattern Recognition 337
  • Artificial Intelligence 243
  • Electrical and Electronic Engineering 110
  • Biomedical Engineering 110
  • Control and Systems Engineering 104
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Fahed Abdallah France View profile →
Citations per field, relative to Wei Song
Wei Song · 1×
Citations per year, relative to Wei Song
Wei Song · 1×

Countries citing papers authored by Wei Song

Since Specialization
Citations

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

Fields of papers citing papers by Wei Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wei Song

This figure shows the co-authorship network connecting the top 25 collaborators of Wei Song. A scholar is included among the top collaborators of Wei 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 Wei Song. Wei 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 3
2 1
3 0
4 2
5 1
6 0
7 1
8 2
9 0
10 5
11 8
12 12
13 14
14 15
15
Digital image semantic segmentation algorithms: A survey
12
16
Violent Scene Detection based on Multiple Instance Learning and 3D Histogram of Oriented Gradients.
1
17
The Critique of Traditional Ontology and Art Ontology
0
18 12
19
The Current Status and Development of WAAS Technique
3
20
On-line Detection Methods of Composite Insulator
11

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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