Kan Wu
Impact in
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- Video Surveillance and Tracking Methods
- Advanced Neural Network Applications
- Advanced Image and Video Retrieval Techniques
- Human Pose and Action Recognition
- Advanced Vision and Imaging
- Visual Attention and Saliency Detection
- Oral Surgery top 10%
- Dental Radiography and Imaging
Papers in
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- Advanced Neural Network Applications 4
- Video Surveillance and Tracking Methods 2
- Advanced Image and Video Retrieval Techniques 2
- Medical Image Segmentation Techniques 2
- Co-authors
- Houwen Peng (3 shared papers)Jianlong Fu (3 shared papers)Hongyang Chao (1 shared paper)Minghao Chen (1 shared paper)Bin Yan (1 shared paper)Huchuan Lu (1 shared paper)Dong Wang (1 shared paper)Li Chen (1 shared paper)
- Journals
- Computers & Graphics (1 paper)IET Image Processing (1 paper)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)2021 IEEE/CVF International Conference on Computer Vision (ICCV) (1 paper)
- Partner nations
- ChinaGermanyUnited Kingdom
In The Last Decade
Kan Wu
10 papers receiving 517 citations
Kan Wu's Hit Papers
Peers
Comparison fields: 5 of 85
- Computer Vision and Pattern Recognition 368
- Oral Surgery 46
- Media Technology 49
- Aerospace Engineering 117
- Artificial Intelligence 116
Countries citing papers authored by Kan Wu
This map shows the geographic impact of Kan Wu'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 Kan Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kan Wu more than expected).
Fields of papers citing papers by Kan Wu
This network shows the impact of papers produced by Kan Wu. 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 Kan Wu. The network helps show where Kan Wu may publish in the future.
Co-authors
The 22 scholars most cited alongside Kan Wu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Rethinking and Improving Relative Position Encoding for Vision Transformer Hit paper breakdown → | 2021 | 224 |
| 2 | 2021 | 148 | |
| 3 | 2022 | 79 | |
| 4 | 2013 | 53 | |
| 5 | 2018 | 13 | |
| 6 | 2018 | 8 | |
| 7 | 2022 | 4 | |
| 8 | Mining Subsidence Prediction Parameters Acquiring with 3D Laser Scanning Data | 2010 | 1 |
| 9 | 2018 | 1 | |
| 10 | 2018 | 1 |
About Kan Wu
Kan Wu is a scholar working on Computer Vision and Pattern Recognition, Information Systems, Artificial Intelligence, Computer Networks and Communications and Control and Systems Engineering, having authored 10 papers that have together received 532 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (4 papers), Video Surveillance and Tracking Methods (2 papers), Advanced Image and Video Retrieval Techniques (2 papers), Medical Image Segmentation Techniques (2 papers), Complex Network Analysis Techniques (1 paper), Dental Radiography and Imaging (1 paper), 3D Shape Modeling and Analysis (1 paper) and Robotics and Sensor-Based Localization (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (368 citations), Oral Surgery (46 citations), Media Technology (49 citations), Aerospace Engineering (117 citations) and Artificial Intelligence (116 citations). Kan Wu has collaborated with scholars based in China, Germany and United Kingdom. Frequent co-authors include Houwen Peng, Jianlong Fu, Hongyang Chao, Minghao Chen, Bin Yan, Huchuan Lu, Dong Wang, Li Chen, Yanheng Zhou and Jing Li. Their work appears in journals such as Computers & Graphics, IET Image Processing, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
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.