Ying Shen
- Computer Vision and Pattern Recognition top 0.5%
- Media Technology top 0.5%
- Artificial Intelligence top 2%
- Signal Processing top 1%
- Experimental and Cognitive Psychology top 5%
- Co-authors
- Lin ZhangHongyu LiYicong ZhouAmirAli Bagher ZadehLouis–Philippe MorencyPaul Pu LiangZhun LiuShiyu Zhao
- Topics
- Advanced Vision and Imaging (15 papers)Robotics and Sensor-Based Localization (15 papers)Image Enhancement Techniques (9 papers)
In The Last Decade
Ying Shen
61 papers receiving 2.9k citations
Hit Papers
Peers
Comparison fields: 5 of 118
- Computer Vision and Pattern Recognition 2.0k
- Media Technology 824
- Artificial Intelligence 589
- Signal Processing 465
- Experimental and Cognitive Psychology 281
Countries citing papers authored by Ying Shen
This map shows the geographic impact of Ying 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 Ying Shen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ying Shen more than expected).
Fields of papers citing papers by Ying Shen
This network shows the impact of papers produced by Ying 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 Ying Shen. The network helps show where Ying Shen may publish in the future.
Co-authorship network of co-authors of Ying Shen
This figure shows the co-authorship network connecting the top 25 collaborators of Ying Shen. A scholar is included among the top collaborators of Ying 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 Ying Shen. Ying Shen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 3 | |
| 6 | 7 | |
| 7 | 32 | |
| 8 | RefineDNet: A Weakly Supervised Refinement Framework for Single Image Dehazingbreakdown → | 244 |
| 9 | 5 | |
| 10 | 15 | |
| 11 | 45 | |
| 12 | 108 | |
| 13 | 5 | |
| 14 | 12 | |
| 15 | Efficient Low-rank Multimodal Fusion With Modality-Specific Factorsbreakdown → | 614 |
| 16 | 1 | |
| 17 | 82 | |
| 18 | 44 | |
| 19 | 8 | |
| 20 | 22 |
About Ying Shen
Ying Shen is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Computer Graphics and Computer-Aided Design, having authored 71 papers that have together received 3.0k indexed citations. Recurring topics across this work include Advanced Vision and Imaging (15 papers), Robotics and Sensor-Based Localization (15 papers) and Image Enhancement Techniques (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.0k citations), Media Technology (824 citations) and Signal Processing (465 citations). Ying Shen has collaborated with scholars based in China, Macao and Sweden. Frequent co-authors include Lin Zhang, Hongyu Li, Yicong Zhou, AmirAli Bagher Zadeh, Louis–Philippe Morency, Paul Pu Liang, Zhun Liu, Shiyu Zhao, Shengjie Zhao and Shengjie Zhao. Their work appears in journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Image Processing.
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.