Guo-Ye Yang
Impact in
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- Advanced Vision and Imaging
- Image and Video Stabilization
- Generative Adversarial Networks and Image Synthesis
- Advanced Image and Video Retrieval Techniques
- Advanced Neural Network Applications
- Advanced Image Processing Techniques
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- Computer Graphics and Visualization Techniques
Papers in
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- Advanced Image and Video Retrieval Techniques 2
- Advanced Vision and Imaging 2
- Image and Video Stabilization 2
- Advanced Neural Network Applications 2
- Face recognition and analysis 1
- Advanced Image Processing Techniques 1
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- Remote-Sensing Image Classification 1
- Co-authors
- Shi‐Min Hu (4 shared papers)Miao Wang (3 shared papers)Song–Hai Zhang (3 shared papers)Guowei Yang (2 shared papers)Dun Liang (1 shared paper)Shao-Ping Lu (2 shared papers)Ariel Shamir (2 shared papers)Ruilong Li (1 shared paper)
- Journals
- IEEE Transactions on Image Processing (2 papers)National Science Review (1 paper)Computational Visual Media (1 paper)Science China Information Sciences (1 paper)Pure (University of Bath) (1 paper)
- Partner nations
- ChinaIsraelUnited Kingdom
In The Last Decade
Guo-Ye Yang
7 papers receiving 277 citations
Peers
Comparison fields: 5 of 47
- Computer Vision and Pattern Recognition 243
- Computer Graphics and Computer-Aided Design 32
- Media Technology 52
- Human-Computer Interaction 8
- Computational Mechanics 29
Countries citing papers authored by Guo-Ye Yang
This map shows the geographic impact of Guo-Ye Yang'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 Guo-Ye Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guo-Ye Yang more than expected).
Fields of papers citing papers by Guo-Ye Yang
This network shows the impact of papers produced by Guo-Ye Yang. 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 Guo-Ye Yang. The network helps show where Guo-Ye Yang may publish in the future.
Co-authors
The 22 scholars most cited alongside Guo-Ye Yang, 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 | 103 | |
| 2 | 2020 | 90 | |
| 3 | 2019 | 50 | |
| 4 | 2018 | 14 | |
| 5 | 2024 | 12 | |
| 6 | 2023 | 9 | |
| 7 | 2022 | 1 |
About Guo-Ye Yang
Guo-Ye Yang is a scholar working on Computer Vision and Pattern Recognition, Media Technology, Automotive Engineering, Hardware and Architecture and Artificial Intelligence, having authored 7 papers that have together received 279 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (2 papers), Advanced Vision and Imaging (2 papers), Image and Video Stabilization (2 papers), Advanced Neural Network Applications (2 papers), Remote-Sensing Image Classification (1 paper), Face recognition and analysis (1 paper), VLSI and FPGA Design Techniques (1 paper) and Advanced Image Processing Techniques (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (243 citations), Computer Graphics and Computer-Aided Design (32 citations), Media Technology (52 citations), Human-Computer Interaction (8 citations) and Computational Mechanics (29 citations). Guo-Ye Yang has collaborated with scholars based in China, Israel and United Kingdom. Frequent co-authors include Shi‐Min Hu, Miao Wang, Song–Hai Zhang, Guowei Yang, Dun Liang, Shao-Ping Lu, Ariel Shamir, Ruilong Li, Peter Hall and Xue Yang. Their work appears in journals such as IEEE Transactions on Image Processing, National Science Review, Computational Visual Media, Science China Information Sciences and Pure (University of Bath).
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.