Lida Zhou
Impact in
- Signal Processing top 10%
- Data Management and Algorithms
- Artificial Intelligence top 5%
- Advanced Clustering Algorithms Research
- Anomaly Detection Techniques and Applications
Papers in
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- Advanced Image and Video Retrieval Techniques 4
- Image Retrieval and Classification Techniques 1
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- Data Management and Algorithms 5
- Co-authors
- Yewang Chen (6 shared papers)Ji‐Xiang Du (5 shared papers)Yi Chen (2 shared papers)Nizar Bouguila (4 shared papers)Songwen Pei (2 shared papers)Cheng Wang (1 shared paper)Naixue Xiong (1 shared paper)Zhiwen Yu (1 shared paper)
- Journals
- Information Sciences (2 papers)IEEE Transactions on Systems Man and Cybernetics Systems (1 paper)International Journal of Medical Sciences (1 paper)Pattern Recognition (1 paper)
- Partner nations
- ChinaCanadaUnited States
In The Last Decade
Lida Zhou
7 papers receiving 400 citations
Peers
Comparison fields: 5 of 79
- Signal Processing 81
- Artificial Intelligence 222
- Computer Vision and Pattern Recognition 134
- Computational Mathematics 3
- Statistical and Nonlinear Physics 59
Countries citing papers authored by Lida Zhou
This map shows the geographic impact of Lida 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 Lida Zhou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lida Zhou more than expected).
Fields of papers citing papers by Lida Zhou
This network shows the impact of papers produced by Lida 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 Lida Zhou. The network helps show where Lida Zhou may publish in the future.
Co-authors
The 25 scholars most cited alongside Lida 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
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 141 | |
| 2 | 2020 | 116 | |
| 3 | 2018 | 69 | |
| 4 | 2016 | 59 | |
| 5 | 2018 | 13 | |
| 6 | 2017 | 3 | |
| 7 | 2023 | 1 |
About Lida Zhou
Lida Zhou is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Artificial Intelligence, Oncology and Aerospace Engineering, having authored 7 papers that have together received 402 indexed citations. Recurring topics across this work include Data Management and Algorithms (5 papers), Advanced Image and Video Retrieval Techniques (4 papers), Advanced Clustering Algorithms Research (3 papers), Algorithms and Data Compression (3 papers), Robotics and Sensor-Based Localization (1 paper), Cancer Immunotherapy and Biomarkers (1 paper), Image Retrieval and Classification Techniques (1 paper) and T-cell and B-cell Immunology (1 paper). The work is most often cited by research in Signal Processing (81 citations), Artificial Intelligence (222 citations), Computer Vision and Pattern Recognition (134 citations), Computational Mathematics (3 citations) and Statistical and Nonlinear Physics (59 citations). Lida Zhou has collaborated with scholars based in China, Canada and United States. Frequent co-authors include Yewang Chen, Ji‐Xiang Du, Yi Chen, Nizar Bouguila, Songwen Pei, Cheng Wang, Naixue Xiong, Zhiwen Yu, Xin Liu and Huazhen Wang. Their work appears in journals such as Information Sciences, IEEE Transactions on Systems Man and Cybernetics Systems, International Journal of Medical Sciences and Pattern Recognition.
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.