Ju Shen

36 papers receiving 970 citations

Ju Shen's Hit Papers

Deep Learning-based Human Pose Estimation: A Survey 2023 · 401 citations
4010+1+2Years since publication100200300400

Peers

Ju Shen
Comparison fields: 5 of 71
  • Computer Vision and Pattern Recognition 742
  • Human-Computer Interaction 35
  • Geology 28
  • Instrumentation 9
  • Industrial and Manufacturing Engineering 35
Replace Luís Salgado with:
Luís Salgado Spain
You Yang China
Jordi Pagès Spain
Jacek Naruniec Poland
Matteo Munaro Italy
Kazunori Umeda Japan
Adrian F. Clark United Kingdom
Yue Ming China
Jan Fischer Germany
Ray A. Jarvis Australia
Ju Shen relative to Luís Salgado Spain Luís Salgado's profile →
Citations per field
00.5×2×4×6×8×9.9×
Luís Salgado · 1×
Citations per year

Countries citing papers authored by Ju Shen

Since Specialization
Citations

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

Fields of papers citing papers by Ju Shen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ju Shen, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ju Shen Line = papers co-authored together Ju Shen links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Deep Learning-based Human Pose Estimation: A Survey
Hit paper breakdown →
2023401
2 2020203
3 2013110
4 201840
5 201336
6 201935
7 202133
8 201314
9 201313
10 201413
11 201413
12 201110
13 20159
14 20156
15 20176
16
Virtual mirror by fusing multiple RGB-D cameras
20125
17 20125
18 20195
19 20174
20 20174

About Ju Shen

Ju Shen is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Computer Networks and Communications, Aerospace Engineering and Hardware and Architecture, having authored 43 papers that have together received 996 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (10 papers), Robotics and Sensor-Based Localization (4 papers), Human Pose and Action Recognition (4 papers), Energy Efficient Wireless Sensor Networks (3 papers), Colorectal Cancer Screening and Detection (3 papers), Speech and Audio Processing (3 papers), Voice and Speech Disorders (3 papers) and Teleoperation and Haptic Systems (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (742 citations), Human-Computer Interaction (35 citations), Geology (28 citations), Instrumentation (9 citations) and Industrial and Manufacturing Engineering (35 citations). Ju Shen has collaborated with scholars based in United States, Vietnam and China. Frequent co-authors include Sen-ching S. Cheung, Chen Chen, Nasser Kehtarnavaz, Ce Zheng, Sijie Zhu, Taojiannan Yang, Mubarak A. Shah, K. Vijayan Asari, He Wang and Jianjun Yang. Their work appears in journals such as Information and Computation, IEEE Transactions on Image Processing, Machine Vision and Applications, Applied Sciences and International Journal of Computer Vision.

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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