Shuda Li
Impact in
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- Advanced Vision and Imaging
- Advanced Image and Video Retrieval Techniques
- Optical measurement and interference techniques
- Human Pose and Action Recognition
- Geology top 10%
- 3D Surveying and Cultural Heritage
Papers in
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- Advanced Vision and Imaging 4
- Advanced Image and Video Retrieval Techniques 2
- Optical measurement and interference techniques 2
- Image Retrieval and Classification Techniques 1
- Geology 4
- 3D Surveying and Cultural Heritage 4
- Co-authors
- Victor Adrian Prisacariu (4 shared papers)Vassileios Balntas (1 shared paper)Bülthoff Chen M (1 shared paper)Zirui Wang (1 shared paper)Andrew D. Calway (3 shared papers)Ankur Handa (1 shared paper)Yang Zhang (1 shared paper)Kai Han (1 shared paper)
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)Lecture notes in computer science (4 papers)Bristol Research (University of Bristol) (3 papers)
- Partner nations
- United KingdomHong KongChina
In The Last Decade
Shuda Li
10 papers receiving 329 citations
Peers
Comparison fields: 5 of 34
- Computer Vision and Pattern Recognition 302
- Geology 58
- Computer Graphics and Computer-Aided Design 38
- Aerospace Engineering 217
- Instrumentation 7
Countries citing papers authored by Shuda Li
This map shows the geographic impact of Shuda Li'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 Shuda Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shuda Li more than expected).
Fields of papers citing papers by Shuda Li
This network shows the impact of papers produced by Shuda Li. 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 Shuda Li. The network helps show where Shuda Li may publish in the future.
Co-authors
The 13 scholars most cited alongside Shuda Li, 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 | 2018 | 162 | |
| 2 | 2020 | 83 | |
| 3 | 2008 | 32 | |
| 4 | 2016 | 19 | |
| 5 | 2015 | 16 | |
| 6 | 2019 | 14 | |
| 7 | 2016 | 4 | |
| 8 | 2021 | 3 | |
| 9 | 2023 | 3 | |
| 10 | 2023 | 2 |
About Shuda Li
Shuda Li is a scholar working on Computer Vision and Pattern Recognition, Geology, Aerospace Engineering, Computer Graphics and Computer-Aided Design and Radiology, Nuclear Medicine and Imaging, having authored 10 papers that have together received 338 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (7 papers), Advanced Vision and Imaging (4 papers), 3D Surveying and Cultural Heritage (4 papers), Advanced Image and Video Retrieval Techniques (2 papers), Optical measurement and interference techniques (2 papers), Image Retrieval and Classification Techniques (1 paper), Computer Graphics and Visualization Techniques (1 paper) and Medical Imaging Techniques and Applications (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (302 citations), Geology (58 citations), Computer Graphics and Computer-Aided Design (38 citations), Aerospace Engineering (217 citations) and Instrumentation (7 citations). Shuda Li has collaborated with scholars based in United Kingdom, Hong Kong and China. Frequent co-authors include Victor Adrian Prisacariu, Vassileios Balntas, Bülthoff Chen M, Zirui Wang, Andrew D. Calway, Ankur Handa, Yang Zhang, Kai Han, Rigas Kouskouridas and Qijun J. Chen. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Lecture notes in computer science and Bristol Research (University of Bristol).
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.