Weida Zhou
Impact in
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- Face and Expression Recognition
- Media Technology top 5%
- Remote-Sensing Image Classification
Papers in
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- Face and Expression Recognition 22
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- Neural Networks and Applications 7
- Advanced Computational Techniques and Applications 4
- Co-authors
- Li Zhang (5 shared papers)Fanzhang Li (6 shared papers)Li Zhang (15 shared papers)Licheng Jiao (18 shared papers)Pei‐Chann Chang (2 shared papers)Jing Liu (1 shared paper)Zhe Yan (1 shared paper)Ting Wang (1 shared paper)
In The Last Decade
Weida Zhou
39 papers receiving 800 citations
Peers
Comparison fields: 5 of 96
- Computer Vision and Pattern Recognition 412
- Media Technology 98
- Artificial Intelligence 341
- Signal Processing 95
- Computational Mechanics 170
Countries citing papers authored by Weida Zhou
This map shows the geographic impact of Weida Zhou'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 Weida Zhou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Weida Zhou more than expected).
Fields of papers citing papers by Weida Zhou
This network shows the impact of papers produced by Weida Zhou. 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 Weida Zhou. The network helps show where Weida Zhou may publish in the future.
Co-authors
The 25 scholars most cited alongside Weida Zhou, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 253 | |
| 2 | 2010 | 88 | |
| 3 | 2012 | 78 | |
| 4 | 2002 | 72 | |
| 5 | 2009 | 45 | |
| 6 | 2013 | 32 | |
| 7 | 2016 | 29 | |
| 8 | 2007 | 23 | |
| 9 | 2017 | 19 | |
| 10 | 2011 | 18 | |
| 11 | 2021 | 15 | |
| 12 | 2002 | 15 | |
| 13 | 2002 | 15 | |
| 14 | 2008 | 13 | |
| 15 | 2015 | 13 | |
| 16 | 2019 | 10 | |
| 17 | 2005 | 10 | |
| 18 | 2009 | 7 | |
| 19 | 2009 | 6 | |
| 20 | 2009 | 6 |
About Weida Zhou
Weida Zhou is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Control and Systems Engineering, Computational Mechanics and Signal Processing, having authored 41 papers that have together received 814 indexed citations. Recurring topics across this work include Face and Expression Recognition (22 papers), Advanced Algorithms and Applications (12 papers), Sparse and Compressive Sensing Techniques (10 papers), Neural Networks and Applications (7 papers), Blind Source Separation Techniques (5 papers), Remote Sensing and Land Use (4 papers), Advanced Computational Techniques and Applications (4 papers) and Fault Detection and Control Systems (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (412 citations), Media Technology (98 citations), Artificial Intelligence (341 citations), Signal Processing (95 citations) and Computational Mechanics (170 citations). Weida Zhou has collaborated with scholars based in China and Taiwan. Frequent co-authors include Li Zhang, Fanzhang Li, Li Zhang, Licheng Jiao, Pei‐Chann Chang, Jing Liu, Zhe Yan, Ting Wang, Li Zhang and Li Zhang. Their work appears in journals such as Knowledge-Based Systems, Neural Networks, Pattern Recognition, Applied Intelligence and Information Sciences.
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.