Dong Shen

400 citations
6 papers · 213 indexed · h-index 3
Topics
Multimodal Machine Learning Applications (2 papers)Human Pose and Action Recognition (2 papers)Domain Adaptation and Few-Shot Learning (2 papers)
Journals
IEEE Transactions on Image ProcessingProceedings of the ... ISARC2022 IEEE International Conference on Multimedia and Expo (ICME)
Partner nations
ChinaSouth Korea

In The Last Decade

Dong Shen

4 papers receiving 204 citations

Peers

Dong Shen
Comparison fields: 5 of 53
  • Computer Vision and Pattern Recognition 135
  • Artificial Intelligence 57
  • Biomedical Engineering 42
  • Media Technology 27
  • Radiology, Nuclear Medicine and Imaging 15
Replace James Gabriel with:
James Gabriel United States
Hezheng Lin China
David Helbert France
M. Radha India
Noel E. O’Connor Ireland
Tingting Yao China
Edouard Oyallon France
Jia Xue United States
Dong Shen relative to James Gabriel United States James Gabriel's profile →
Citations per field
00.5×10×20×30×35×
James Gabriel · 1×
Citations per year

Countries citing papers authored by Dong Shen

Since Specialization
Citations

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

Fields of papers citing papers by Dong Shen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dong Shen

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

All Works

6 of 6 papers shown
#WorkIndexed citations
1 1
2 128
3 62
4 21
5
3D Reconstruction of Scale-Invariant Feature for Mobile Robot localization
1
6 0

About Dong Shen

Dong Shen is a scholar working on Computer Vision and Pattern Recognition, Health Information Management and Artificial Intelligence, having authored 6 papers that have together received 213 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (2 papers), Human Pose and Action Recognition (2 papers) and Domain Adaptation and Few-Shot Learning (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (135 citations), Media Technology (27 citations) and Artificial Intelligence (57 citations). Dong Shen has collaborated with scholars based in China and South Korea. Frequent co-authors include Xiangyu Wu, Hezheng Lin, Cheng Xing, Deng Cai, Hao Feng, Minghao Chen, Haifeng Liu, Xiaofei He, Shuai Zhao and Toshihiro Nishimura. Their work appears in journals such as IEEE Transactions on Image Processing, Proceedings of the ... ISARC and 2022 IEEE International Conference on Multimedia and Expo (ICME).

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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