Ke Shen

868 total citations
37 papers, 484 citations indexed

About

Ke Shen is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Ke Shen has authored 37 papers receiving a total of 484 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Computer Vision and Pattern Recognition, 15 papers in Artificial Intelligence and 13 papers in Signal Processing. Recurrent topics in Ke Shen's work include Advanced Data Compression Techniques (13 papers), Video Coding and Compression Technologies (9 papers) and Topic Modeling (8 papers). Ke Shen is often cited by papers focused on Advanced Data Compression Techniques (13 papers), Video Coding and Compression Technologies (9 papers) and Topic Modeling (8 papers). Ke Shen collaborates with scholars based in United States, China and Hong Kong. Ke Shen's co-authors include Edward J. Delp, Lawrence A. Rowe, Mayank Kejriwal, Alex X. Liu, Eric Torng, Paul Salama, Jianping Wang, Qingfeng Huang, Leah H. Jamieson and Hing Cheung So and has published in prestigious journals such as Nature, Nature Communications and PLoS ONE.

In The Last Decade

Ke Shen

35 papers receiving 443 citations

Peers

Ke Shen
Comparison fields: 5 of 65
  • Computer Vision and Pattern Recognition 319
  • Signal Processing 233
  • Computer Networks and Communications 93
  • Artificial Intelligence 70
  • Electrical and Electronic Engineering 50
Replace Jia-Shung Wang with:
Jia-Shung Wang Taiwan
Mengbai Xiao United States
Hwai-Jung Hsu Taiwan
Matthew Broadbent United Kingdom
Tianchi Huang China
Xiaochen Lian China
Jamie Hayes United Kingdom
Ya-Qin Zhang China
Brian J. Matt United States
Benjamin Zi Hao Zhao Australia
Jia-Shung Wang Taiwan View profile →
Citations per field, relative to Ke Shen
Ke Shen · 1×
Citations per year, relative to Ke Shen
Ke Shen · 1×

Countries citing papers authored by Ke Shen

Since Specialization
Citations

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

Fields of papers citing papers by Ke Shen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ke Shen

This figure shows the co-authorship network connecting the top 25 collaborators of Ke Shen. A scholar is included among the top collaborators of Ke Shen 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 Ke Shen. Ke Shen 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 7
2 3
3 1
4 0
5 4
6 8
7 4
8 1
9 1
10 9
11 7
12 6
13 26
14 14
15 2
16 4
17 110
18 19
19
A study of real-time and rate scalable image and video compression
11
20 46

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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